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Harold Van Colt

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NBSIR 77-1403

A STANDARD ERGONOMICS

REFERENCE DATA SYSTEM: THE

CONCEPT AND ITS ASSESSMENT

Harold P. Van Cott

Joel J. Kramer

Valmon J. Pezoldt

Louis G. Porter Charles Fried

John V. Fechter

J. J. Persensky

Human Factors Group

Consumer Sciences Division

Center for Consumer Product Technology

National Engineering Laboratory

National Bureau of Standards

Washington. D.C. 20234

Warren H. Teichner

Department of Psychology

New Mexico State University

Las Cruces, New Mexico 88003

June 1978

Final Report

Prepared for Institute for Applied Technology

National Bureau of Standards

U.S. DEPARTMENT OF COMMERCE, Juanita M. Kreps. Secretary

Or. Sidney Harman, Undor Sacretary

Jordan J. Baruch, Assistant Sacratary for Scianca and Tachnoiogy

NATIONAL BUREAU OF STANDARDS. Ernest Ambler, Acting Director
II
TABLE OF CONTENTS

Pa^e

List of Figures iii

List of Tables iii

Acknowledgements ........ v

Executive Summary vii

1. INTRODUCTION 1

2. SYSTEM CONCEPT 13

3. USER NEEDS FOR ERGONOMICS DATA 25

4. CRITICAL EVALUATION 29

5. NATIONAL ERGONOMICS SURVEY 49

6. DATA PROCESSING AND OUTPUT ............. 81

7. PRELIMINARY SERDS PROGRAM PLAN 85

APPENDIX A ................. Ill

APPENDIX B .............. 129

APPENDIX C 157

i
i

I

f
LIST OF FIGURES

Number Title Page

1 Standard Ergonomics Reference Data System

(SERDS) — A Possible Configuration 21

LIST OF TABLES

Number Title Page

1 Data Requirements of Potential SERDS Users . . 28

2 Classes of Performance 31

3 Categories of Information Extracted from the

Literature ...... 33

4 Plan for Management and Operation of SERDS . . 86

5 Plan for National Ergonomics Survey 93

6 Plan for Critical Evaluation of Published

Ergonomics Data 9 8

7 Preliminary Estimate of Required Resources for

SERDS (FY 78-83) 103

iii

ACKNOWLEDGEMENTS

The authors are grateful to many individuals and groups

within the Federal, industrial and academic communities for

their help in shaping and directing the concept described here

for a Standard Ergonomics Reference Data System. Although not

all of our silent collaborators can be mentioned, special

appreciation must be extended to a few.

Julien M. Christensen, Chairman, Department of Industrial

Engineering, Wayne State University (Detroit, Michigan) and

Richard W. Pew, Principal Scientist, Bolt, Beranek and Newman

(Cambridge, Massachusetts), in their role as consultants,

provided many useful comments on the initial concept and draft

of this report. Warren H. Teichner, Department of Psychology,

New Mexico State University (Las Cruces, New Mexico), also a consultant, prepared material on which most of Chapter 4 of

this report is based. Robert White, of the Army Natick

Laboratory, provided invaluable information and guidance on

all matters related to anthropometric measurement.

Stanley I. Warshaw, Director, Center for Consumer Product

Technology; Melvin R. Meyerson, Chief, Product Systems Analysis

Division; Carl 0. Muehlhause, Senior Scientist, Institute for

Applied Technology; and Stephen A. Rossmassler, Program

Manager, Office of Standard Reference Data, all of the National

Bureau of Standards, gave generous, helpful advice and support.

Finally, we wish to thank Kim Leaman, Pam Tyeryar and

Bonnie Matteson for their most helpful secretarial support.

Forums for the discussion of our concept were graciously

provided by numerous groups and organizations. Mention of

them appears elsewhere in this report. To them all we also

owe an important debt for their help.

V

EXECUTIVE SUMMARY

Today's consumer and worker expect to buy goods and work with

products and equipment that function well within human

capacities. To meet this expectation industry and government

must be able to draw upon current, reliable ergonomics (human

factors engineering)* data representative of the range of human

characteristics to which technology must conform.

At present, limited amounts of ergonomics data are collected

to meet specific, immediate needs. These data collection efforts

are uncoordinated and unstandardized. Data that exist are of

uneven quality, contain inconsistencies, inaccuracies and gaps,

and are often unsuitable for general reuse. The net results are

products, systems and equipment that may be unnecessarily unsafe,

unreliable and unsatisfying to the user.

During the pilot study reported here, the Human Factors

Section of NBS examined the needs of industry and government for

ergonomics data, assessed the scientific and technical challenges

to be met in meeting these needs and proposed a preliminary plan

for development and operation of an ergonomics data system.

Major findings and conclusions derived from this pilot study

are that:

1. A definitive survey of user needs and

priorities is necessary in order to define

the scope of the system.

2. Standards must be developed for the

definition of units, measurements,

measurement methods and reporting of data.

3. An assessment of alternative technologies

for capturing, storing and processing

ergonomics data must be made to identify a cost-effective approach.

4. Data derived from the published ergonomics

literature and from a national ergonomics

survey must be critically evaluated before

they are systematically compiled and

disseminated.

5. Provision must be made for the orderly

management of system development.

*For a mere comprehensive definition of ergonomics, see footnotes

on bottom of pages 2 and 5.

vii

f
6 . A period of three years would be required before

data would be available to users.

7. An assessment must be made of the utility of the

system and its capabilities in order to help ensure

system responsiveness to the user community.

The data base proposed here owuld provide, for the first

time, a single point of access to reliable and current

anthropometric, behavioral and physiological data for application

to technology design.

viii
1. INTRODUCTION AND OVERVIEW

The ultimate expression of an effective technology is an

information source from which may be drawn data and relationships

which answer technical questions and against which hypotheses and

issues of feasibility may be resolved. Such an information

source would ideally contain, after a process of critical

evaluation, all of the usable data required by technology and be

amenable to quantitative operations of many kinds. Such a source

would also serve to indicate the absence of information and,

thereby, provide a picture of needed research.

The Data Source of the Physical Sciences

The important role played in the development of

technology by a source of critically evaluated data from the

physical sciences and engineering has long been recognized by

government, commerce and industry. Today, collections of

selected and evaluated numerical data on the properties of

substances and materials are being developed in data analysis

centers around the world. These centers extract, evaluate,

organize and publish data from the scientific literature on

topics ranging from the properties of neutrons and crystalline

substances to the elastic characteristics of metals and alloys.

Topics are selected for treatment to match the needs of a spectrum of users. When gaps in existing data or data of poor

quality are discovered, research may be commissioned to fill the

void. Evaluated data are made available to users from a single,

central access point.

In the United States, a Congressionally mandated portion

of this system is known as the National Standard Reference Data

System (NSRDS) managed by the National Bureau of Standards (NBS)

NSRDS generates outputs for its users in the form of monographs,

critical reviews, printed tables of critical data and computer

tapes. Users of these outputs come from all sectors of commerce,

industry, government and the academic community.

Such a system has several benefits. The availability of

information from a central point saves a user time in searching

for needed data and, with the addition of the critical evaluarion

function, reduces the likelihood that erroneous or inaccurate

information will be employed. The probability of repeating

research that has already been conducted is decreased. In

addition, the criteria used in the critical evaluation process

along with the standards of quality exemplified by its outputs

have a subtle but important impact on the quality of new research

and research reporting.
NSRDS is linked with similar data systems in other

countries. Together, these national data systems comprise an

international data secretariat known as CODATA (Committee on Data

for Science and Technology of the International Council of

Scientific Unions) . Along with national data systems, CODATA is

a potent force in the diffusion of accurate, physical science and

engineering knowledge into the stream of technological advance

that has become vital to the world's economy.

The Data Source of the Human Sciences

While the information needs of commerce and industry

were a stimulus to the development of a data system for the

physical and engineering sciences, until recently the "human

science^" have not had a similar stimulus to develop a comparable

system. Instead, they have continued to pursue traditions of

information exchange and publication well-suited to the needs of

the scholarly academic community but ill-designed to make

available the selected data about human characteristics needed to

link and shape technology to its human users. Today, one is

confronted with a large and growing literature that is not being

fully exploited for reuse either to the advantage of the human

sciences or to the benefit of technology. It is not our purpose

to speculate why this is the case. Instead, it is instructive to

consider the human sciences in historical perspective as they

have been put to the service of technology and examine the

inadequacies of the information mechanisms that have been used.

The term "human sciences" is used here to encompass the

scientific disciplines concerned with the study of human

behavior and functioning: anatomy, anthropology,

experimental psychology and physiology. Recently, several

applied disciples have developed from the human sciences.

"Engineering anthropometry" is concerned with the measurement

of the static and dynamic characteristics of the body as it

occupies and moves in space and as the human body applies

force to objects. Engineering anthropometry is derived from

physical anthropology, anatomy and physiology. "Biomechanics"

a related term, deals with the physics and engineering of

human movement and the impact of physical forces upon the

body. "Engineering psychology," "human engineering" and

"biotechnology" focus on human information processing and

action and with the conditions that affect the accuracy,

reliability, precision and speed of response. "Human factors"

and "ergonomics" are often used to encompass all of these

applied fields.

2
Historical Perspective

The application of knowledge of the anthropometric and

psychological characteristics of man to the design of tools,

instruments, equipment and systems is so ancient that it is

surprising that the notion has been rediscovered only recently.

Folk norms for the design of tools for digging, cutting

and shaping developed very early in man's history (Drillis,

1963) . These devices employed rules of thumb about the size of

the hand, grasp of thumb and fingers, the length of the arm, and

certain biomechanical properties to establish the lengths,

configuration and moments of inertia of hand implements.

Technology was being shaped by the characteristics of its users.

Perhaps because of the close relationship between early

man and his tools, natural units of measurement first developed

around the hand, fingers and foot. Only much later did physical

units of measure replace them. These natural units are still

used in many cultures: "le pied" and "le pouce" in French, "il

peide" and "il pollice" in Italian, and "peda" and "pirksts" in

Latvian have the same measurement implications as "foot" and

"hand" in English (Drillis, 1963). Units such as these served

well for centuries. The norms of people had become design

criteria for the technology of the time. In the Middle Ages, for

example, the "thumb-ell," a distance measured across the hand to

the tip of the outstretched thumb of a chief (14 to 18 cm) was

applied to the design of the handles of files, swords and jugs.

Although folk norms were used for centuries, there was

no necessity to obtain precise measurements of the dimensions of

individuals until the development of body armor created the need

(Roebuck et al. 1975). It might be said that the science of

"anthropometry," or body measurement, began at that time.

The behavioral and physiological characteristics of man

also figured prominently in the history of tool and instrument

design. The radius of action and speed of stroke for farm

implements were enhanced by adjusting handle length to optimize

the kinetic energy that could be used for striking activi-cies.

The latency of human response to a stimulus (reaction time)

became an important factor in the design of precise astronomical

measuring devices.

Although differences in the body dimensions, strength

and performance capabilities of different races had been observed

by Marco Polo over the period 1273-1295, an interest in taking

accurate measurements of the characteristics of large groups of

-3
individuals did not occur until the 18th Century with the work of

Linne and Buffon. This interest took a practical bent when

statistics on the body dimensions of military recruits were used

to size uniforms.

By the time of the Industrial Revolution, the use of

folk noms had been replaced by the development of statistical

tables and charts of selected human characteristics required to

meet the needs of mass markets for furniture as well as clothing.

One of the first systematic attempts to measure the performance

characteristics and body dimensions of a large sample of the

population of a nation was made by Sir Francis Galton. For a period of five years, in a laboratory at the London Health

Exposition, detailed, quantitative measurements were made of the

visual, auditory, psychomotor and anthropometric characteristics

of over 9000 Exposition visitors. Among the measures taken were:

the speed and force with which individuals could strike a blow;

the highest audible frequency that could be heard; the reaction

time to a stimulus; and the ability of individuals to

discriminate objects of different weights (Galton, 1883).

Although Galton was one of the first in recent history

to recognize the implications for technology of the measurement

of human characteristics representative of a population, little

was done of a practical nature to exploit the notion. However,

the Gilbreths (Frank and Lillian of Cheaper by the Dozen ) recognized the value of placing work withm easy reach of the

operator and initiated a study of work space dimensions (1917) . In the same tradition, F.W. Taylor (1947) began to apply a number

of behavioral principles to workplace design. LeGros and Weston

(1926) were the first to do systematic studies of workplace seat

design. Later, Lay and Fisher (1940) did detailed research on

seat angles and comfort. Hooton (1945) conducted a large scale

survey of the railroad-riding public, measuring over 3000

individuals in the Boston and Chicago railroad stations to

develop criteria for seat design.

By World War II, military technology had become so

complex that it had pushed many human functions to the limit.

The problems were many. One has only to examine the cockpits of

the aircraft of that time to appreciate the information

processing, decision-making and environmental stress loads placed

upon pilots by some designs. Instruments were frequently located

in areas too remote to be easily reached or accurately read. A

myriad of displays, designed with little regard for human use and

limits, filled the cockpit workspace. Exotic environments—high

altitudes and low temperatures, noxious fumes and exposed

electrical and mechanical hazards —degraded performance, health

and safety to the detriment of individuals and sensitive military

missions

.

4
In response to these problems, increasing numbers of

psychologists, physiologists, anthropologists, physicians and

industrial engineers were invited from the academic community to

work as part of design teams. Soon a new interdisciplinary

field, "ergonomics,"^ began to emerge, and a large body of

theory, research and data began to accumulate. An additional

impetus was given to broadening the scope of ergonomics by the

man-in-space program. Later, concern about highway traffic

fatalities extended ergonomics into still another area.

By 1963, the amount of activity and the volume of

literature in ergonomics had reached a level at which it became

increasingly difficult to solve problems based upon existing

data. Recognizing that the mechanisms for identifying, assessing

and using published material were inadequate to the task, the

Human Factors Society, a professional focus in the U.S. for the

discipline, conducted a searching examination of the information

system that then existed and attempted to pinpoint its

inadequacies and suggest solutions. Among the proposals

generated, several are worthy of note (Ronco 1963) :

"(1) Greater commitments ... to report information

promptly and explicitly as circumstances

permit. .

(2) That documentation centers ... undertake the

individually impossible task of acquiring and

organizing the existing literature...

(3) The support of... systems for the dissemination of

relevant information by a variety of

techniques (e.g., critical reviews, annotated

bibliographies, and data sheets).

(4) ...periodic review of the accrued wisdom in the

field not only to decide what is valuable and

should be perpetuated, but also decide what is

worthless and ought to be thrown out."

The term "ergonomics" is credited to W. Jarzebowski who first

used the term in Nature and Industry in 1846. Its roots are

Greek: "ergon" to work and "nomos" meaning natural laws.

5
Growth and Status of Ergonomics Information

Ronco (1963) and his colleagues have noted that the

problem of improving the state-of-the-art in any applied

scientific field has the following three aspects: (1) validating

new knowledge, (2) combining that information into a data base,

and (3) disseminating that knowledge to its users. Each of these

merits further examination here in order to discover the

strengths and weaknesses of the mechanisms associated with the

field of ergonomics, conditions that still exist today 15 years

later.

Validating New Knowledge

Quality control of published material in the human

sciences has been accomplished by means of two mechanisms timehonored by the academic community: (1) peer review prior to

initial publication and (2) the sifting and winnowing for the

best research results that takes place as texts and monographs

summarizing the published literature are prepared. Since there

have been no explicit criteria for the specification of the

conditions of research or the reporting of observations, research

of uneven quality has been published, and the bad along with the

good has been memorialized in the archives of the discipline.

As ergonomics began to emerge as a distinct human

science discipline, much of its funding came from Federal

agencies that required the publication of technical reports prior

to any other form of publication. This introduced an additional,

advantageous process of review and improved the quality of

reported work. Furthermore, the lack of page limitations in

technical reports facilitated more complete reporting.

In the late 50 's, military standards and specifications

for the application of ergonomic information and data to the

design of equipment and systems were written and mandated for

most government contractors. These standards tended to encourage

the adoption of common research paradigms and methods and

introduced greater uniformity in the conduct of research and

reporting

.

Despite the fact that these mechanisms have improved the

quality of ergonomics data, they still fall short of providing

the systematic, critical evaluation and validation of data needed

for today's technology. Critical reviews of ergonomics research

are still few in number and there are no formally established

information analysis and evaluation centers as there are in some

6
other sciences. However, some encouraging individual attempts

have been made to critically evaluate and integrate research

results. An example of one method of critically evaluating

ergonomics data, prepared for this report by Warren H. Teichner,

New Mexico State University, is presented in Chapter 4 to

illustrate the process.

Combining Information into a Data Base

Several types of data bases exist in ergonomics as in

other disciplines: (1) the published literature itself, (2)

bibliographic aids containing citations, abstracts and indexes to

the literature and (3) manuals, guides, handbooks and other

compilations that suiranarize the basic data and methods of the

field. Except for the lack of explicit criteria for reporting

the results of research and describing experimental conditions,

the existing journal and technical report literature in

ergonomics serves well as a channel for the dissemination and

archival storage of work in the field.

Existing ergonomics bibliographic aids and services are

an effective means for locating needed references in the summary

literature. Ergonomics Abstracts , started in the 60 's when

publication of the Tufts Annual Human " Engineering Bibliography

ceased publication, is a principal service. In addition,

Psychological Abstracts , Biological Abstracts , Engineering Index,

the Defense Documentation Center , the National Technical

Information Service and the Smithsonian Scientific Information

Exchange provide additional coverage of ergonomics and related

literature. However, these reference works provide no indication

of the quality of cited sources. Citation of the existence of a critical review of an article does not accompany the citation of

the article itself as is done in some bibliographic services such

as Mathematical Reviews . Nor do existing ergonomics

bibliographic references employ data flags or tags to indicate

the presence of data or measures of a given type in an article—

practice being adopted by some of the bibliographic services of

the physical sciences and engineering.

Although a number of reference guides and manuals

summarize the basic data and methods of important areas of

ergonomics research, those existing guides and manuals —such as

the Bioastronautics Data Book (Webb, 1964) and Human Engineering

Guide to Equipment Design (Van Cott, 1972) —focus on the special

problems of man in military and space systems and cannot usually

be generalized to the many new, non-aerospace areas, such as

consumer products, which ergonomics has entered in recent years.

7
Dissemination of Knowledge

The many dissemination mechanisms —'journals, technical

reports, bibliographic services and reference manuals —that exist

today in ergonomics remind one of the problem of a child faced

with an overabundance of food. His problem is not one of hunger,

for there is far more than can be eaten, but of knowing what will

best satisfy his needs from the abundance before him. Something

is still missing.

In summary, there is an abundance of ergonomics

literature of uneven quality. That literature is largely

oriented around the ergonomics problems of the military and

aerospace industries. There are gaps in data for many new nonmilitary applications. The research that does exist has not been

critically evaluated, organized around the needs of its users or

integrated to reveal existing relationships. Numeric data are

not always available or easily located for reuse, and lack of or

incomplete descriptions of the conditions under which they were

obtained makes the comparison of results difficult. As interest

and concern for the health, safety, comfort and satisfaction of

the consumer and the worker have increased, the need for

ergonomics data of high quality and covering a variety of generic

problem areas will undoubtedly increase. Having high quality

ergonomics data implies that such data are expressed in

functional form, based on ratio scales, and that such data are

usable in various design engineering trade-off situations.

Specialized Ergonomics Data Bases

Within the U.S. a number of data bases are in various

stages of development to meet specialized ergonomics data needs.

At the Sandia Laboratories, A.D. Swain has established a human

error rate data bank for use by military/aerospace system

planners and designers and by reliability analysts and

ergonomicists (Swain, 1970) . At the Aerospace Medical Research

Laboratory at Wright-Patterson Air Force Base, Ohio, Charles E.

Clauser and his colleagues have been instrumental in establishing

an Anthropometric Data Bank which incorporates at a single center

current, U.S. military anthropometric data in comparable formats

based upon many surveys (McConville, et al., 1977). These are

two examples of ergonomics data bases focused on either

specialized populations or around relatively restricted problem

areas. Another development which came to the authors' attention

as this report was being written is the Habitability Information

Analysis Center being proposed by Dr. Roger Brauer and Robert

Dinnat, Construction Engineering Laboratory, Champaign, Illinois.

8
Although specialized data bases of this type undoubtedly

meet a need, their proliferation creates problems for the user

who seeks a single point of access. They do not resolve the

problem of providing a convenient single interface between the

multiple users of ergonomics and a source of critically evaluated

data.

The notion of developing an ergonomics data base to meet

the needs of the technology of a nation is not unique to the

United States. Efforts with similar aims are underway in other

countries. In the Soviet Union, Vladimir Mounipov, Deputy

Director of the Institute of Technical Aesthetics, VNITTE,

Moscow, is collaborating with other Socialist East European

countries on a common data base leading to an ergonomics data

bank (Seminara, 1977) . A Human Biometry Data Bank being

developed under the direction of M.A. Coblentz of the Laboratory

of Appled Anthropology, Rene Descartes University, Paris, France.

This data bank, supported by the Directorate of Research and Test

Facilities, is currently limited to selected anthropometric

measurements. However, Coblentz envisions its expansion to cover

other ergonomic data in the future (Coblentz, 1976). In Mexico

plans for the orderly assembly of ergonomics data representative

of the Mexican population are being developed.

It can be anticipated that similar developments will

take place in other industrial countries as nations become

increasingly concerned with the safety, comfort and satisfaction

of their citizens. For example, the July-August 1977 issue of

Information Hotline indicates that the South African Bureau of

Standards has established an Ergonomics Information Service to

make human factors data readily available to local industrial

research organizations and educational institutions.

A single example illustrates the need experienced by

U.S. industry for current, evaluated ergonomics data,

particularly physical anthropometry. For years many segments of

industry have relied upon the results of the 1939-40 Department

of Agriculture anthropometric survey of the U.S. population

(O'Brien and Shelton, 1941) for data on which to base the design

and sizing of products, systems and clothing. However, as diet,

exercise and other factors have altered the body dimensions of

the population, these data have become obsolete and no longer

represent the dimensions of today's child or adult. For example,

between 1946 and 1977 significant changes have taken place in the

average body dimensions of U.S. Army women ( Human Factors

Bulletin, 1977)

9
I

The problems caused by the lack of current, accurate

anthropometric data have remained unsolved. Instead, industry

has had to make do with trial and error and attempts to

extrapolate from military anthropometric data to the general

civilian population. The problem has been costly for both

industry and consumers. One major clothing retailer, for

example, estimates that its annual loss from garments returned

because of poor fit exceeds $175 million.

In 197 3 concern over this problem was intensified by the

prospect of conversion to metric measurements. Attempts to make

a direct conversion from U.S. to metric measures were singularly

unproductive. As a result, 50 leading designers, engineers,

quality control experts and officials from commerce, industry,

government and professional organizations met in Washington, D.C.

to discuss the matter and explore ways in v/hich the problem might

be resolved.

Following that meeting the participants wrote letters to

various members of the NBS staff, including its Director,

expressing an urgent need for a national anthropometric survey. . Based upon these inputs NBS ' Institute for Applied Technology

requested its Technical Analysis Division to perform a preliminary study of user need, organization, potential scope,

and cost of a national anthropometric survey. This culminated in

a report addressing these issues and proposing that a national

anthropometric survey be conducted by NBS to collect the needed

data (Steinberg, 1974)

.

It was determined that while the Center for Health

Statistics, Department of Health, Education and Welfare has the

conduct of surveys as a part of its mission, such surveys are

limited to the collection of measurements that are health

related. Thus, many of the measurements needed for cTothing,

product and system design are not presently included.

Furthermore, the Department of Agriculture, which had conducted

the 1939-40 survey, is no longer staffed and equipped to collect

the needed data.

10
In the Fall of 1976, the NBS Institute for Applied

Technology funded the Human Factors Section of its Center for

Consumer Product Technology (CCPT) to undertake a second pilot

project. The proposal for the new proiect had been endorsed by

the Center's external Evaluation Panel and work started in

January 19 77. The aim of the new project was to explore the

feasibility of an ergonomics data base that would include not

only anthropometric but other ergonomic data as well.

Beginning in February 19 77 and continuing throughout

the duration of the study, project staff described the concept

of a Standard Ergonomics Reference Data System to representatives

of industry, government and the research community at a series

of professional and scientific symposia and specialized meetings

organized at NBS. The consensus of participants was that the

proposed concept would serve the purpose of improving product

and system design.

In its August 1977 report, the CCPT Evaluation Panel stated

"There is a considerable lack of statistical data pertinent

to the human animal that are necessary for optimum design of

consumer products. This is true, and other organizations, in

both the public and private sectors, are concerned about

it . . . Representative Yatron from Pennsylvania contemplates

legislation to develop important basic dimensions of the

American Citizen. It would be appropriate for CCPT to direct

such a study, if it is undertaken."

11

2. SYSTEM CONCEPT

The primary aim of a Standard Ergonomics Reference Data

System (SERDS) is to provide a single source of critically

evaluated, numerical data on selected human characteristics for

use in the planning, design, test and setting of standards for

the man-machine interface and environment of equipment, systems,

consumer products and buildings. A second aim is to advance the

level of ergonomics research by developing standards for

ergonomics measurement and reporting.

A Model System

Is there a model for SERDS? In 1963, the Federal

Council for Science and Technology requested NBS to assume

primary responsibility in the Federal government for promoting

and coordinating the critical evaluation of numerical data in rhe

physical sciences. The program was conceived as a decentralized

national effort with financial support deriving from a variety of

government and private sources but with NBS responsible for

overall planning and coordination. This allowed existing NBS

data compilation activities to be strengthened, new projects to

be initiated in neglected technical areas, and the entire effort

to be molded into a coherent program (Rossmassler , 1975) . When NBS accepted responsibility for the National

Standard Reference Data System (NSRDS) , it established an Office

of Standard Reference Data to manage the program. This office

performs several functions:

•- Allocation of that part of the NBS budget

spent on critical evaluation within NBS and by

contracts to outside groups.

•: Monitoring of all projects that are supported

by NSRDS.

• Management of a publications program and a limited information service. ^ Assessment of domestic and international

efforts to detect duplication and encourage

coverage of important technical areas.

•> Performance of research and development on

computer handling of data and in the

application of automated procedures to the

activities of data analysis centers.

13
The compilation and critical evaluation of physical

science data by NSRDS take place at data analysis centers on a continuing basis or through the "one-shot" compilation of

critical reviews by individual scientists or small groups of

collaborators. The one-shot efforts supplement the long-term

bibliographic and analysis skills of the data analysis centers

(Rossmassler , 1975).

A goal of the Office of Standard Reference Data has been

to establish data centers in all technical areas which fall

within the scope of NSRDS. These centers focus upon data areas

for which there is a high intensity of demand or need.

The scope of each NSRDS data analysis center is not only

need-oriented but is restricted to data that can be wellcharacterized and defined in terms of accepted physical theory.

Such restrictions undoubtedly leave out data for which there are

recognized needs but which are not amenable to clear-cut

evaluations

.

The products of NSRDS are derived from the regular

search of the physical science literature, retrieval and indexing

of papers of interest, and the extraction of numerical data for

analysis and dissemination. Outputs of this process cons'ist of

tables of data, critical reviews of specific areas, magnetic

tapes of selected data and responses to specific requests for

data and information. Some NSRDS data analysis centers have

large, computer based files from which bibliographic data and

citations can be retrieved. The centers are able to respond to

requests for specific information from interested users.

The budgets of NBS and several other Federal agencies,

support from industries with interests in specific types of data,

and fees from the dissemination of copyrighted NSRDS publications

in the Journal of Physical and Chemical Data help maintain NSRDS.

Guidance to the NBS Office of Standard Reference Data is

provided by a series of advisory committees formed under the

auspices of the National Academies of Science and Engineering and

the National Research Council. Since NSRDS has operated

successfully for well over a decade, its organization and

functions are useful for planning an ergonomics data system.

14
Functional and Organizational Requirements of SERDS

An examination of the NSRDS model reveals that several

conditions must be met to achieve a collection of useful,

critically evaluated ergonomics data. These include:

User Needs - The needs for ergonomics data

must be surveyed to identify the type of data

required, the terms used in defining these

data, and the measurement unit, precision and

accuracy necessary for specific applications.

These needs must be further examined to

isolate those that are generic to a variety of

areas in which the application of data is

expected to generate a substantial economic or

social benefit. The long-term development of

the system must rely upon some scheme of

setting priorities for the orderly and

sequential development of data modules

organized around those generic need areas.

• Data Input - Identified needs must be compared

with existing data to determine which demands

can be met from the existing supply and which

will require new research. • Critical Evaluation - Both existing and new

data must be critically evaluated against

explicit criteria (presently under

development) to be eligibile for inclusion in

the system.

» Data Processing and Output - Evaluated text

and data from published sources must be

processed and presented in output formats

convenient for users. Processing may entail

statistical computation, model development and

use, data extrapolation and logical

manipulation of data and text.

• Voluntary Standards - Standards for future

ergonomics research must be developed for the

definition of terms, units of measurement and

measurement procedures to be used by the

research community in generating new data.

• System - A system for meeting these conditions

must be developed to manage and coordinate the

acquisition, evaluation, processing and

dissemination of ergonomics data.

15
Scope of SERDS

As is presently envisioned, the scope of SERDS would be

initially restricted to well-defined anthropometric, behavioral,

physical and physiological characteristics of normal-healthy men,

women and children. Although this definition leaves out many

borderline cases and rejects others, the intent is to concentrate

on human characteristics which can be clearly defined in terms of

existing theory and measurement practice. Characteristics that

lack a solid foundation in theory, description and measurement

would not be included. The focus of SERDS will be the

application of ergonomics data to technological problems. With

the above considerations in mind, several classes of data can

tentatively be defined as being appropriate for SERDS:

Anthropometric Data - This class would initially include

static measurements of the dimensions of the human body as a function of age, sex, occupation, ethnic origin and other

demographic variables. Measures of the forces that can be

exerted by muscle groups on physical objects would also be

included for selected generic tasks. Measures of body

proportions, contours, areas and volumes would be added when

adequate measurement technologies have been developed and

standardized. Data on the dynamic characteristics and movement

of body members, such as inertial properties and static reach

envelopes would be selectively included as data become available.

Data would be collected not only on the adult male population but

on females and children of both sexes. Women and children have

been badly neglected in most past anthropometric studies.

Sensory Capability Data - This class would deal with the

ability of human visual and auditory systems to. detect,

discriminate and recognize signals and signal patterns. Data on

other sensory capabilities, such as those involving the

cutaneous, kinesthetic, proprioceptive and vestibular senses,

would be admitted if they are needed and can be readily

characterized

.

Performance and Performance Reliability - This class

would be limited to simple, easily-measured and wellcharacterized aspects of human performance and performance

reliability that occur frequently in operating man-built products

and system^s. Examples include: (1) simple and choice reaction

times to signals and messages, (2) other components of human

performance required of individuals in the use of switches,

knobs, dials, keyboards and other manually manipulated

objects/products and (3) information processing and decisionmaking as they occur in definable system contexts.

16
Physiological and Psychological Tolerance Data - This

class of data would include measurements of the effects of such

variables as toxic substances, noise and temperature that enhance

or degrade performance, comfort, and physiological well-being.

The classes of data defined above are based on

suggestions made by the various groups contacted in the course of

this study and on the authors' judgments derived from past

experience at NBS and elsewhere. Such judgments must be regarded

as provisional in nature and subject to future modification.

SERDS Input

The principal inputs to SERDS would come from two

sources

»' Data and information selected from the

published literature of ergonomics and related

sciences

» A national ergonomics survey of selected

anthropometric and behavioral characteristics

utilizing a representative sample of the U.S.

population.

The measurements taken in the survey would be limited to

either those that are not covered in the present literature or

are not representative of the U.S. population. Chapter 5

(National Ergonomics Survey) discusses the requirements for a national ergonomics survey and the technological and sampling

challenges to be faced in survey planning and conduct.

Inputs from both sources must necessarily include

bibliographic and descriptive information that permits each

information source to be identified, describing the theoretical

and procedural basis used to obtain the reported data. Numerical

data alone are subject to gross misinterpretation and misuse

unless these conditions have been met at the input stage.

Critical Evaluation

Critical evaluation of data required by SERDS will be

accomplished by means of one or more critical evaluation and

analysis centers. These evaluation centers would be located in

Federal, academic or not-for-profit institutions that have been

selected for expertise in bibliographic and data analysis in

given subject matter fields.

17
Chapter 4 (Critical Evaluation) of this report describes

an approach to critical evaluation that has been successful in

evaluating and validating knowledge in several ergonomics fields.

Here, however, an important point should be made. For the

scientist, knowledge derives from observations made under

specified conditions. Description of these two aspects of

knowledge, the observations and the specified conditions,

represents two different, but important kinds of data of

scientific interest that are essential elements in the process of

critical evaluation. One has no meaning without the other.

Observations or measurements may be summarized by means of a

variety of units. Specified conditions include quantitative

values of independent variables, control factors and experimental

arrangements and procedures. Thus, a distinction can be made

between those data that are the results of a scientific effort

and those descriptive data which indicate the conditions under

which the data were obtained.

Some scientists tend to believe that the reliability of

the numerical results of anthropometric and behavioral studies is

unacceptably low at almost any level of precision. It is our

contention, however, that anthropometric and behavioral results

at an appropriate level of precision and accurately described in

terms of independent variables, are sufficiently reliable for

effective use as an information source.

While it is also contended that the human sciences have

not yet achieved the degree of rigor of the physical sciences,

there have been many successful applications of human science

data to applied problems. In short, if behavioral and

anthropometric data can be used to resolve problems related to

human safety, comfort and satisfaction then it is worthwhile to

improve the process. Critical evaluation alone will not solve

all of the problems of ergonomics, or any other science, but it

can enhance the validity, reliability and utility of ergonomics

data and save users from doing this most difficult task by

themselves

.

Data Processing and Output

Chapter 6 (Data Processing and Output) of this report

reviews the requirements for SERDS data processing and output.

However, several general summary comments should be made here on

the types of data processing that will be required.

The variability (both within and among individuals in a given population) of anthropometric measurements and behavioral

traits leads to the generation of large quantities of statistical

18
data. These data can be reported as raw measures obtained for

each participant and as summary statistics that describe the

properties of distributions of measurements for all participants

measured. If they are reported in complete form, raw data may be

used to establish relationships and develop models not reported

in the original research. Raw data may be used, for example, for

extrapolation or be combined with new data to obtain a larger

sample of measures for analysis. Although it is not the present

practice of researchers to publish raw data, in our opinion this

practice must be encouraged in order to fully exploit and reuse

the research results that now exist. The large capacity and low

cost of computer storage now make this possible.

Many human behavioral, anthropometric and biomechanical

properties can be expressed by computerized, mathematical models.

There are three general types of models. One is a "man-model"

that serves as a reservoir of behavioral or anthropometric data.

This model allows for greater versatility in storing,

manipulating and retrieving information than is possible with

printed data tables. A second model is rhe "reactive" model that

responds to external events or forces such as visual srimuli or

vibration. This model requires that selected, dynamic properties

of an organ or human subsystem (e.g., the arm or other body

segment) be characterized. The model becomes "reactive" through

incorporation of external stimuli or stressors. A third type of

model is the computerized analog of man in a work station or

environment (office, home or vehicle) . Computerization is

achieved by defining properties of the environment to represent

the location and characteristics of a number of alternative

workplace configurations. For anthropometric applications, the

dimensions of specially- formed components such as seats or

controls can be included in the model. For behavioral

applications, the information to be processed by an individual

from a display can be included in the model (Roebuck et al .

1975) . As it is now envisioned, data processing would include

the capability to exercise existing models of each type using the

SERDS numerical data base.

Another essential function of the SERDS data processing

system is to perform logical operations on the data base. These

operations may consist of relatively simple routines for the

search and retrieval of bibliographic descriptors of interest to

more complex routines for performing mathematical and statistical

computations and combining data. The most common requirements

for combining data will be to (1) develop statistical

distributions and intercorrelation matrices, including derivation

of a composite population distribution from the distributions of

several known populations, (2) estimate an unknown measurement

19
distribution by the addition, subtraction or application of some

other combinatorial process to two or more known measurement

distributions, and (3) calculate the group mean, standard

deviation or other statistics.

SERDS Configuration

Although SERDS could be configured in a variety of ways,

a promising approach at this point appears to be that of the

National Standard Reference Data System described earlier in this

chapter. Figure 1 represents a proposed configuration for the

system.

Data obtained by means of continuing searches of the

existing, published literature and data from a national

ergonomics survey will be the inputs to the system. SERDS itself

will be comprised of several data analysis centers operated under

the general policy guidance of a SERDS Office. This office, the

secretariat of the system, will receive policy guidance from an

independent Advisory Panel and act upon proposals for system

operation. A User Council representative of the system's users

will also provide input to the office regarding system updating

and improvement needs. Output of SERDS to government, industry

and other research users will be provided by the SERDS Office.

Feedback from users of the system will be employed in all phases

of SERDS operation: the data to be selected, the criteria to be

employed in data and system evaluation, and the formating of

outputs for convenience of use.

It is anticipated that some SERDS users will encounter

difficulties in converting SERDS data into a form suitable for a specific application. Raw anthropometric data,, for example,

require additional processing in order to arrive at acceptable

sizing standards and tariffs for the manufacture of clothing.

Clothing tariffs indicate the proportion of a given size in a population and determine the number and mix of persons to be

measured. The SERDS data base will require additional

manipulation by a specialist sufficiently familiar with such

applications to be able to make the necessary translations. For

this reason, a link between SERDS and its users —called

Translation Support—must be included at the user interface.

This support would be available when the requirement for a particular form of data translation exists.

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21
Data Analysis Centers

Within the United States, a number of "centers of

excellence" now exist in specialized ergonomics areas. Candidate

SERDS data analysis centers will be selected from these centers

of excellence. Some of these candidate centers focus upon the

work of a particular investigator, several of whom now perform

critical evaluation to advance their own research. Other centers

have gone beyond critical evaluation into the development of

specialized data bases. These are bibliographic centers that

maintain comprehensive reference files of citations or literature

in a given area or centers that maintain data bases of numerical

information on a particular ergonomics topic. No major obstacles

are foreseen in the selection of qualified organizations to serve

as data analysis centers from among the pool that now exists.

Advisory Panel and User Council

In order to ensure that system policies are developed

which reflect current and projected national needs for ergonomics

data, an Advisory Panel will be established, comprising 10 to 15

outstanding leaders representative of the field of ergonomics and

of ergonomics interests as they exist within commerce, industry,

government and the research community. This panel would meet at

least annually to review the SERDS program, to assess its

effectiveness and to propose policy for its structure and

function.

A sample of the user community will constitute a User

Council. The council, consisting of delegates from each

sustaining user group, will meet at least annually to advise the

SERDS Office and its Advisory Panel on actions to be taken with

respect to the scope, funding, operation and effectiveness of the

system. The User Council will also be the principal focal point

for the development of standards for the collection and reporting

of ergonomics data. Unlike the ergonomics standards activities

of standards setting organizations, such as the American National

Standards Institute (ANSI) and the International Standards

Organization (ISO) , which center around ergonomic standards for

particular products or systems, the standards activity of the

User Council will focus upon criteria for the collection of

ergonomics data rather than data application. This activity is

seen as nonredundant and complementary to the activities of

present standards setting organizations.

22
SERDS Office

Throughout the pilot project, various proposals for the

location of the secretariat for SERDS were discussed with

potential users in government and industry. Several alternatives

were suggested: (1) an existing standards organization, (2) the

National Science Foundation (NSF) , (3) the National Center for

Health Statistics of the Department of Health, Education and

Welfare (NCHS/HEW) , (4) a private organization, (5) a new

organization established specifically for the purpose, and (6)'

the National Bureau of Standards (NBS) . Each of these

alternatives has advantages and disadvantages and each will be

examined in detail to help ensure that a suitable locus is

selected as the permanent "home" for SERDS.

Funding Sources

Until a detailed assessment has been made of user needs

and data priorities, an accurate estimate of the funding required

for the front-end development or subsequent operation of SERDS

cannot be given. However, for the initial development of SERDS,

which would entail several efforts of a planning nature,

potential funding sources include:

m- NBS Scientific and Technical Research Support

(STRS);

» Support from other Federal agencies interested

in participating in SERDS development.

Looking to the future, beyond FY 78, in addition to the

above sources, other support for further development and

operation of SERDS could come from the following

» Support from trade associations or a consortium of industries interested in SERDS

use. This support could take two forms:

effort applied by industrial personnel on

temporary assignment to SERDS (industrial

fellowships) or direct monetary subsidies;

• Fees from users for receiving SERDS products

and services;

Fees from the sale of copyrighted material

sold by SERDS. (NSRDS has established a precedent for this practice)

•> Special congressional appropriation.

At this point, there is no clear =cut, definitive way in which the

required timing, magnitude or mix of support from these potential

sources can be projected.

23

3. USER NEEDS FOR ERGONOMICS DATA

Among the most important factors determining the success

or failure of the ergonomics data system proposed in this report

is the degree to which the system meets the data needs of its

users. Clearly, the most sophisticated, up-to-date and

comprehensive data base is of value only to the extent that it

fulfills identifiable needs. Early in the pilot project effort

it was recognized that a thorough assessment of these needs for a wide spectrum of potential users was essential, both to define

the scope of the system and to assign priorities to the various

types of data such a system might include.

The need for anthropometric and other ergonomic data was

first addressed at a meeting in 1973 with representatives of the

Federal government, industry, trade associations and researchers.

Although that meeting, summarized in the report of a feasibility

study of a national anthropometric survey prepared by NBS

(Steinberg, 1974) , pointed out the urgent need for up-to-date

anthropometric data, further assessment of these needs was deemed

necessary for the SERDS effort. A formal user needs study,

proposed in Chapter 7 of this report, is planned for FY 7 8 to

satisfy this requirement.

Although a comprehensive assessment of needs could not

be performed in the course of the pilot project, a preliminary

effort was undertaken, primarily by conducting a series of

meetings with a variety of potential users from the industry,

government and research communities. These meetings served both

to inform the various groups about the SERDS pilot project and to

solicit information about the data needs of potential users.

Summary of Meetings

Four major briefings were held with representatives of

the following organizations:

March 16, 1977 - Sizing Committee of the Mail Order

Association of America

March 25, 1977 - NBS Behavioral scientists from the

Center for Building

Technology, Center for

Fire Research and the

Auditory Acoustics Section

25
March 29, 1977 - Twelve Federal government agencies

including: Army Natick

Research & Development

Command; Army Research

Institute; Army Human

Engineering Laboratory;

Consumer Product Safety

Commission; Defense

Nuclear Agency; General

Accounting Office;

National Institute of

Aging, NIH; National

Science Foundation;

Occupational Safety and

Health Administration;

Office of Consumer

Affairs, HEW; Office of

Naval Research and the

U.S. Postal Service

June 7, 1977 - Management and technical staff of

the Association of Home

Appliance Manufacturers

In addition to meetings held specifically to solicit • potential user interest and needs, several other technical and

scientific organizations have been made aware of the SERBS

concept through personal contact or presentations at conferences

and technical sessions. Although these contacts were not

established for the sole purpose of assessing the needs for

ergonomic data, many expressions of need were brought to the

attention of the project staff during and after the presentation

sessions. Among the groups contacted were the Society of

Automotive Engineers, American Apparel Manufacturers Association

Technical Forum III, Engineering Foundation Safety Conference,

and the Consumer Product Technical Interest Group of the Human

Factors Society. Major SERDS symposia were held at the 1977

Annual Convention of the American Psychological Association in

August, the 21st Annual Meeting of the Human Factors Society in

October and the Canadian Human Factors Society Meeting in

November. Minutes of two of the meetings described above can be

found in

project are contained in Appendix B. Appendix C contains

remarks made at the March 2 9 meeting by the external consultants

to the project: Dr. Julien M. Christensen and Dr. Richard W.

26
As a result of these initial meetings and technical

presentations, a substantial level of interest has been

identified for the SERDS concept and for a variety of types of

ergonomics data. The major needs identified from these sources

have been summarized in Table 1. Those general areas of need

which were expressed repeatedly are listed along with some

examples of the specific data needs within these broad areas and

potential applications of the data.

Given the obvious importance of continuously assuring

that SERDS is responsive to the needs of its users, it is

essential that the assessment of user needs does not end with the

initial identification of data needs resulting from the proposed

one-year needs study. Therefore, as SERDS becomes operational, a mechanism must be developed which will provide repeated, periodic

reassessments of required data. Although such a mechanism has

not been clearly defined at this point, two important sources for

this information can be noted. First, the Users Council

described in Chapter 2 will provide key guidance to SERDS

management in this area. In addition, monitoring of the number

and type of requests for data from SERDS will also provide

information useful in the reassessment of data needs.

27
DATA

AREA of NEED

Static Anthropcxnetry

Dynamic Ant±iropcroetry

Strength Characteristics

Physiological

Characteristics

Senscry/Perceptual

Processes

Tolerance to

Environrrental Conditions

Reaction Time

Information Processing/

Cognitive Functicns

Capabilities of

Special Populations

Table 1

REQUIREMENTS OF POTENTIAL

SERDS USERS

SPECIFIC DATA NEEDED

Basic human body dimensions

as function of age/sex etc.

Bending & stooping capabilities, reach dimensions

Static & dynamic force

measurements, lifting,

pushing & pulling

capabilities

Aerobic S anaerobic

capacity, maximal heart

rate, expiratory volume

Measures of visual & auditory acuity, color

vision

Exposure tolerance to physical

& chemical agents, e.g.

tolerance to high intensity

light, noise, tCTiperature,

radiation

Simple Si complex reaction

time to a variety of

stimuli

Interpretation of syirtxfls,

learning processes,

memory

Anthropanetric , sensory,

physiological measures of

children, aged, handicapped

DATA APPLICATION

Design of tools & other

hard goods, develoanent

of clothing sizing & tariffs

Control location & operation, ^rkspace design

Equipment & job design for

industrial workers, product portability design

Environmental design, job

specification ; toxici t^,' levels

Design of controls,

digital displays, visual

& auditory warning signals

Protecticn of workers and

environmental design

Display-control relationships; blade stopping

time

Design of displays,

signals , instructional

materials , training

devices

Product & environmental

design

28
4. CRITICAL EVALUATION

Implementation of the SERBS concept advanced in this

report requires a mechanism for the critical evaluation and

selection of existing data for inclusion in the system. Readers

of individual articles are often, though not always, provided

with the appropriate caveats and qualifiers to the uses and

origins of the reported data. Users of data handbooks are less

likely to be exposed to such cautions or to remember them even if

present, as published data compilations tend to achieve an aura

of respectability whether deserved or not. Data retrieved from a

computerized system often acquire even greater "respectability."

Therefore, it is incumbent upon the builders of a data system to

assure the validity of the data in the system (Kissman, 1975) . Unless the methodology and conditions of each candidate

publication are critically evaluated, proper qualifiers cannot be

tagged onto the data.

Data evaluation becomes even more critical in light of

one of the advantages of numeric data bases : the potential

capability to recombine data for reuse in new application areas.

Without critical evaluation of the data input to SERDS , it is

conceivable that the system could provide a dangerous disservice

to users by providing easy access to "bad" or misleading data.

Granting the need for critical evaluation of data, the problem

addressed in this chapter concerns the mechanisms for

accomplishing such evaluation.

It has been suggested previously that Data Analysis

Centers be established and charged with the responsibility for

compilation and evaluation of specified, limited areas of data.

One criterion for the selection of a particular organization as a Data Center would be demonstrated, resident expertise in the

subject matter area(s) of interest. The importance of careful

selection of these Data Centers cannot be overemphasized since,

in any evaluation procedure, the role of subjective, expert

judgment is crucial. Lide and Rossmassler (1973) recognized the

importance of informed, subjective judgement in the evaluation of

physical science data when they stated:

"While any evaluation of data published by others

should be as objective as possible, a certain

amount of subjective judgment on the part of the

evaluator is difficult to avoid. In every field

of science there are individuals and laboratories

known for their careful, consistent work, while

others develop a reputation for undependable

results and frequent mistakes. Likewise, some

29
authors describe their research clearly and

precisely, while others omit details needed to

make an independent value judgment. Such

factors should be taken into consideration when

assigning a weight to a given piece of

published data, but it is difficult to do

this in a quantitative, completely objective

way." (p. 149)

Warren H. Teichner and his colleagues at New Mexico

State University have employed a procedure for developing an

information source for certain areas of human performance which

may serve as a general prototype for the critical evaluation and

compilation process. This procedure relies heavily on

subjective, expert judgments within a framework designed to be as

objective as possible.

Teichner and his colleagues' original interest in the

information source concept arose from needs for their own

research. After several years of developing a procedure aimed at

meeting specialized needs, the feasibility of such a procedure

for general use became apparent and had also been demonstrated.

Based upon certain previous speculations, Teichner and

Olson (1971) hoped to use the quantitative results of the

published literature in an absolute sense to establish functional

relationships and models which would express the dependence of

measures of human performance on the major variables to which

they are related. Rather than search for those investigations

which might provide the most comprehensive treatments and base

relationships solely on the findings of one or two such studies,

they attempted to base the relationships on trends that might be

fitted across the results of all relevant, acceptable

investigations

.

Table 2 presents a listing of topic areas which were

defined as those of interest, and within which an attempt was

made to solve specific problems. To reduce the effort to a manageable scope, the problems were each defined narrowly. For

example, all relationships of interest were to be restricted to

those involving simple visual stimuli in "noiseless" situations.

Once relationships were developed for these simple situations,

these relationships were expanded to deal with more complex

stimuli and situations.

Even with such a narrow scope the question was whether

the large literature relevant to each of the situations of

interest could be organized into a manageable form for

30
Table 2. Classes of Performance

Defining Measure

Probability

of Detection, PCD^)

Probability

of Detection, P(D)

Search Time, t.

Percent or

number correct,

% C. Hr

Percent or number correct,

% C,

Percent or

number correct,

% C,

Sensory

Reaction Time

or Latency, RT

Reaction or Decision Time,

CRT

Percent

Time-on target,

RMS Error, etc.

More than one of

the above; either

% C, P(D), or time

Class Name

Sensory

Searching

Searching

Unlimited

Searching

Uni dimensional

Coding

Multidimensional

Coding

Translation

or Receding

Simple

J^eaction

Time

Choice Reaction

Time (CRT)

Tracking

Complex

Task

Brief Description

Signal detection in the absence of

signal uncertainty

Signal detection in the presence of signal

uncertainty (spatial, temporal, frequency of

occurrence, noise) and a limited search time.

Searching, but with an unlimited time

available for target acquisition.

Attachment of a name or other unique response

to an attribute of a stimulus, e.g., color,

pitch, direction, shape, position, letter,

digit.

Attachment of a name to a collection of

stimulus attributes or of separate events or

items, e.g., "John" for a person; flower,

fleet, "attack" for a battle procedure, etc.

Use of a syntax, or set of rules, or other

predefined relationship between two codes to

relate or transform names or codes. S-S

translations involve a transformation from

one stimulus code to another; S-R translations

involve a transformation of a stimulus code to

a response code; R-R translations are between

response codes.

Time from initiation of a signal in a sensory

searching task to initiation of the detection

reaction.

Time from initiation of a signal to initiation

of response in a searching or coding task

having signal uncertainty or more than one possible signal.

Alignment of response to a changing input.

Combinations of the above carried out

successively or simultaneously.

In addition:

1. Measures of sensitivity include: Absolute threshold (aI), Relative

threshold (aI/I), d' , psychological scale values.

2. Measures of accuracy include Infoniiation Transmitted.
quantitative analysis. To know that the conditions of different

experiments were reasonably comparable required Teichner and his

colleagues to establish some means for extracting detailed

information from each paper, and to devise a coding scheme for

subsequent collation. Furthermore, because of the enormity of

the literature to be searched in a relatively short time, it was

necessary that the information to be extracted be systematized so

clearly that the process of extraction could be accomplished by

supervised assistants. For this purpose a set of descriptive

terms and definitions was established to provide a system for

computer storage of the descriptive specifications of human

performance studies. The terms underwent revision as variations

were encountered in the literature. Table 3 presents the terms

in their most recent form.

Since they are restricted to situations involving visual

inputs, the terms employed represent only the foundation of a descriptive data base of human performance. Nevertheless, with

that constraint, if one had that portion of the total literature

of interest coded as shown in Table 3, studies could be collated

and sorted in a large number of ways to find those which provide

exactly the information desired. Otherwise, it would have to be

concluded that the information is not available. If, in

addition, the actual numerical data of those studies were

available, i.e., the results base, various computations utilizing

the data could be undertaken in an attempt to derive, or try to

arrive at, quantitative answers to any problem. For example, one

might simply want the average value of a dependent variable for

all studies having a specified set of conditions, or desire a least squares fit of a particular function for all such studies

represented, across values of a particular independent variable.

Whether or not one were successful in manipulating the

descriptive and results bases would depend not only on how much

between-exper iment variability was present, but also on at least

two other critical conditions: (1) whether the available studies

provide sufficient descriptive information, and (2) whether the

problem had, in fact, been made sufficiently specific for it to

be answered in a reasonable way. In addition, success would

depend upon having considerable expertise in the particular

problem area when the information source was prepared in order to

insure (1) that the appropriate information had been extracted

and put into comparable terms, and (2) that low quality

experimental reports had been rejected. The total process is

illustrated in the following sections and some of the products

resulting from use of the system are discussed.

32
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The human performance information source that was

developed should not be confused with the use of it. The

intention was to arrive at functional relationships in certain

subject-matter areas of human performance. Where data were

available, they were used in the general manner indicated. When

they were not available, hypothetical relationships were

postulated in order to develop models of human performance. The

degree to which one is willing to deviate from available

information in a particular case depends on the purpose and in no

way reflects on the adequacy of the information source for other

cases, uses or users.

For each topic there is a descriptive base on IBM cards

and a results base in the form of a book which provides the

actual figures, graphs and tables contained in the source

articles. Where only figures were available, the data were read

from the figure to generate a table of numerical results.

Studies in the results base are identified by the same study

number used in the descriptive base. Thus, the results base in

book form can actually be used by itself in a limited way. All

of the human performance results bases have been produced in book

form.

For computational work, data were selected by

descriptive specification for a particular purpose (s). However,

in their most recent effort, Teichner and his colleagues

intermixed the results and descriptive data to obtain a single

printout. This could be done easily because the data reported in

the area were standardized in form and limited in scope. Keeping

in mind the restricted scope of their effort, the following human

performance information sources were developed:

1 . Sensory Probability of Visual Detection : Contains those studies which report both the threshold and a measure of variability for detecting the visual stimulus as a function of brightness, contrast and size.

2. Simple Visual Reaction Time : Contains those

studies of the reaction time to a flash of light in central

vision

3. Complex or Choice Reaction Time : Contains

those studies using simple, familiar, visual signals and manual

or verbal responses.

4 . Probability of Signal Detection as a Function of

Time: This contains the vigilance literature for simple targets.

39
5. Visual Search for a Simple Target : Contains

those studies which have used simple targets in unknown positions

under both "natural" and laboratory conditions.

6. Coding : Studies of errors in reporting the

contents of briefly exposed displays.

7. Complex Searching : An expansion of #5 above

which includes complex target situations.

8. Eye Behavior and Measurement : Contains

studies concerned with the measurement of eye movements and other

visual parameters.

Zach of the above-listed analyses deals with important

empirical and theoretical problems. In the following paragraphs,

the major aspects of one of them is reviewed as a specific

example of the application of the system.

Simple reaction time (RT) to a flash of light has been a matter of both practical and theoretical scientific concern for

at least 150 years. It touches on every aspect of human endeavor

including scientific observation itself. Mathematical models

have been proposed which, unfortunately, have been based upon

limited experimental findings. This problem was selected not

only because of its long history and general importance, but

because its theoretical background is easy to summarize.

It has been known for a long time that RT is inversely

related to stimulus intensity and apparently varies with stimulus

duration, warning signal - test signal time interval

( f oreperiod) , whether vision is monocular or binocular and a number of other factors. It has been supposed, but never

successfully demonstrated, that RT is a constant for a constant

product of intensity and time (duration) and, thereby, follows

Bloch's law for threshold vision.

Theoretically, it has been well-accepted for at least

100 years that RT consists of two components, one of which is a constant neural-muscular transmission lag and the other is a variable time which in turn depends on intensity and other

factors. Thus, RT is generally understood to depend on the time

needed for sensory processing of a signal. More complex

information processing involving such activities as stimulus

identification and problem solving is supposed to take place in a

tim.e period following the sensory processing. Thus, to determine

the time required for more complex processing, it has been common

to subtract the RT to the stimulus (measured separately) from the

total time to process. Teichner ' s analysis of choice reaction

time provided a strong basis for questioning these assumptions.

At the same time the analysis provided useful empirical relationships

.

40
The first step in dealing with the RT problem was to

conduct a fairly quick review of the literature to assess the

descriptive variability with which studies were reported and to

determine if there would be any special information-extracting

problems. With decisions made on this basis, the following

specific assumptions were made and restrictions imposed as a basis for accepting any particular report:

1. Viewing was restricted to central vision.

2. Studies which did not specify either monocular

or binocular viewing were assumed to have been

binocular.

3. The spatial position of the signal had to be a constant and known by the subject.

4. The time of arrival of the signal had to be

known by the subject within close tolerance.

Studies using both random and nonrandom

foreperiods were accepted if it could be

assumed for the former that the subjects were

well-practiced.

5. There could be only one possible signal and

one possible response.

6. The report had to provide either the actual

values of luminance, duration, visual angle

and background luminance, or information from

which those values could be calculated.

7. The procedures and experimental design had to

provide unconfounded data.

In addition, with certain exceptions, the literature sources were

restricted to papers in English.

Restriction #7 above, clearly, is one which draws upon a combination of expertise in the problem area and of knowledge of

experimental design. Though this restriction was judgmental to a considerable degree, inadequate studies had to be isolated in

advance of any attempt tc use their data or to include them in

the information source. In attempting to organize data within a topic, one may find that the results of a particular study

deviate markedly from other studies which used essentially

similar control levels, and that a new reading of the paper may

(or may not) reveal problems with the study that had not been

noticed earlier. These issues are addressed in greater detail

below on the general problem of avoiding error.

41
Acceptance of studies was not only specific to criteria

of the sort listed above but also was restricted to studies which

either provided results in a quantitative form or which were

theoretical or review articles. For the latter, only the

reference was provided along with a code indicating that the

paper was of the theoretical or review kind. Experimental

studies which did not provide actual results (figures or tables)

were not referenced, although they could have been. For those

that provided only figures, the values of the figures were read

from the curves to create a table of numerical values. Some

studies which provided results were rejected either because they

failed to provide enough descriptive information with which to

determine the critical values of control and experimental

conditions, or for quality reasons. Rejected studies were

included in the descriptive base by reference only and with a code indicating that the study had not been accepted. This was

particularly true of studies which could be rejected by a quick

skimming of the paper. The primary concern at that time was in

assuring that already rejected papers were not re-read.

At the time, Teichner and his colleagues were concerned

only with the data base as a tool for their own use. Later, as

other researchers became aware of what was being done and with

the encouragement to be more inclusive, all studies which had

been analysed to some degree and then rejected were included.

Occasionally, this even turned out to be useful to the system,

developers. For example, after completing a particular analysis

using only studies which provided information about critical

experimental conditions, Teichner discovered that some of those

conditions were not really critical. This sometimes depended

upon the precision of measurement in the field. Today RT , for

example, is commonly measured in milliseconds. In any case, it

was sometimes found that intensely studied variables had small,

though statistically significant effects, which, compared to the

effects of other variables, were negligible. Thus, Teichner

could come back to a study rejected because it failed to reoort

on that variable and find that it compared favorably with the

overall trend of studies which did.

Teichner and his colleagues searched for and analysed

papers, using an early version of Table 3. Every conceivable

source was used including standard bibliographic services (e.g.. Library of Medicine) and standard abstracting periodicals. The

bibliographic services proved to be an almost total loss for this

activity and every other search conducted. More pertinent

information was obtained from Psychological Abstracts and

Biological Abstracts than from the total listings for a topic

from other bibliographic services. Generally, Teichner was lucky

42
if a total listing provided two useful references. His

experience might have been different if he tried to obtain

references covering problems of wider scope than the particular

problems selected, e.g., in terms of the whole categories of

Table 2.

It was difficult for Teichner and his colleagues to

estimate the time required to complete a search since all work on

it was part-time. However, their coarse estimate for the topic

of RT was two to three months. Analysis of the studies using

Table 3 required an estimated average of 30-60 minutes, depending

upon the clarity of the paper and the detail provided, with a range of perhaps five minutes to two hours. Sometimes an

important methodological detail would be hidden in the

discussion; sometimes calculations had to be made either because

they had not been, or because the author's calculations were

questioned.

Teichner and his associates learned to avoid reading

anything but method sections until everything in those sections

required by Table 3 was completed as far as possible. They

learned to look first at the experimental design and, if the

design confounded the variables of interest, the paper was

summarily rejected. On the other hand, Teichner and his senior

colleagues felt that they could not entrust that decision to

assistants, even first-year graduate students. Consequently, the

students were required to analyse the paper as far as possible

otherwise. Decisions about experimental design as well as any

other judgment of quality, e.g., adequacy of controls, were made

by senior personnel.

Every paper that could be found was examined.

Sometimes, a useful paper had a far-removed purpose. For

excunple, RT has been used extensively to study personality,

effects of hypoxia, noise and in many other ways. The author's

reasons for using RT were considered totally irrelevant.

There is also the matter of statistical testing. As a policy, statistical findings were completely ignored. (Table 3

does not have this category.) The reasoning was that, depending

on risk level, such tests apply to the expectation that a single

experiment would provide the same data if replicated. Since the

literature was being used to replicate, such tests tend to be

meaningless

Differences in procedures and methods of analysis were

accepted as possible error. If one study reported median RT and

another mean RT the differences were accepted as variations in a

43
single statistic due to random error. Similarly, for other

problems, the use of different psychophysical procedures was

disregarded and variations in threshold were treated as though

they were due to chance. If, however, the results had not been

integrated across studies, those differences would have been

looked at as a possible important source of noise. However,

those differences never turned out to be important when

considered against the variations among a large number of values.

For the simple reaction time problem, the literature

from 1886 to 1971 was searched, applying the criteria noted

above. It was difficult to estimate how many studies were

actually reviewed, since a great many of them were rejected at

the first reading. However, a total of 37 studies was accepted

for inclusion in the descriptive base and 3 5 in the results base.

Not all of those studies provided complete, descriptive

information, but they did at least provide what appeared to be

acceptable data and a majority of the required items of

descriptive information. Of the descriptive base only 14 studies

provided informaticn which was considered to be sufficiently

complete, and which also met the first five restrictions noted

above

.

The procedure of analyzing the data from the 14 studies

was the same as that applied to all of the other analyses. In

this case, most computational work was done by hand although it

could have been done by computer. For some other analyses

calculations were programmed in Fortran and computer plots

obtained. However, only the toxicology study had all of its work

done by computer. In all other cases, some degree of manual work

was involved. Some additional explanation is needed since in all

cases, the work could have been done by computer.

The explanation lies in the individual differences among

researchers. Teichner has the conviction that he could not fully appreciate the possibilities of the data unless he plotted the

data, tedious though that was. The task of organizing data as he

and his associates have done is a creative process often

requiring more time than all previous steps and, at least for

them, the process is stimulated by hypotheses formed in the

course of plotting an unfolding trend. Hypotheses can often be

evaluated quickly by starting new plots. Use of the computer

seems to reduce involvement with the data and discourage the testing of a succession of probe-like hypotheses. But this may

be a matter of temperament rather than of necessity.

The first step in analysing the RT data, as with the other human performance data, was to assume that the measure of interest (here RT) depends entirely on one independent variable

44
The data were then ordered with respect to that variable

regardless of what studies they represented. Without exception,

the resulting plot was chaotic, but did allow for inspection to

detect patterns in the scatterplot representing the effects of

other variables. If such patterns were found, or if the general

findings of the literature suggested, a second variable was

selected and a new plot of the first variable with the second as

a parameter was made. The general plan was to do this

systematically until some combination of variables organized the

data into meaningful trends. There are powerful multivariate

techniques which would permit this whole process to be

accomplished quickly. Such methods, however, produce best fits

of polynomials with no a priori rationalization. The purpose was

to build rational models rather than to merely organize, as such

models are needed to extend the data to other applications or

regimes

For the RT data, the first step was to plot RT relative

to stimulus luminance. RT as a function of both intensity and

time was the next plot. Size of stimulus and monocular versus

binocular viewing were considered next. Finally, stimulus size

was held constant, and RT was plotted separately for monocular

and binocular modes, as a function of time (duration) with

luminance as a parameter.

In doing this, faster RTs were found for monocular than

for binocular data, a completely unreasonable result. After much

data manipulation and rechecking studies, it was decided that the

binocular data must be more reliable. Accordingly, mathematical

functions were fitted to the binocular data for two different

signal sizes: 0.5 degrees of arc and signals that were foveal,

but whose area was larger than the fovea. In each case, a family

of curves could be fitted with luminance as the parameter. The

fits had some empirical value, but suffered because the best

fitting functions were different and the fits were good only

within narrow limits of the variables. Nevertheless, these

analyses were completed because the results had the practical

value of providing a knowledge of their limits.

The next step was to combine luminance and time into a single scale of stimulus energy. When this was done Teichner

discovered that: (a) the binocular data were now faster, a reasonable result; (b) area, in the range available, had only a small effect; (c) Bloch's law does not hold for RTs; and (d) all

of the data fell into two parallel trends, i.e., a monocular

trend of stimulus energy and a binocular one.

45
The work to this point had not proved fruitful for the

construction of models based on single variables, the general

theoretical activity in the literature. The energy function

which combines two variables was promising for practical use, but

still not satisfying theoretically. However, a response

criterion model for latencies in general was available which

could become very powerful if it fit the data. The weakness of

the model was the unavailability of a dependent measure to

represent the response criterion. However, with a simple

mathematical derivation it was possible to show that the

criterion scale could be expressed as the amount of energy in the

stimulus accumulated to the time of the response. All of the

experimental results, regardless of any other specification, were

then plotted with this measure calculated from the data, as a function of stimulus duration with luminance as a parameter. The

result was that all of the data were rather neatly organized.

A final point is in order about the RT study as an

example of an application of the information source. The

literature surveyed covered a long period of time. Yet, only 35

studies (results base) with data of interest were found. Of

these, only 14 were available in detail and in a form permitting

data manipulation. Considering the many hundreds of RT studies

done over the period studied, this would appear to be a remarkably small number. That would not have been the case,

however, had the journals required some form of standard

reporting, perhaps along the lines of the content of Table 3.

Clearly, it would be easy for such information to be coded and

packaged even in a journal article. Information considered

especially important could be given further presentation in the

paper. Some such approach would ensure that all of the relevant

descriptive information needed to replicate the study was

available. Incidentally, attempts were made on a few occasions

to get information directly from authors. The effort was

discouragingj those that responded generally did not have

information about the details of a study published some time

earlier

.

Actually, the small number of studies available for use

is less important than the fact that studies were found for which

it was reasonably certain that the data were collected under the

conditions of interest. It should be noted that the number of

studies available for such use will vary with the topic. The

choice reaction time literature provided 149 studies for the descriptive base and 84 for the results base. The Teichner

analysis used 59 of those studies. On the other hand, the eye behavior information source contains 244 studies in the descriptive base and 55 in the results base. Of all of those

46
studies only 14 contained both eye movement and performance data.

Unlike the 14 RT studies, however, these 14 varied so widely m

task and in ocular parameters reported that nothing could be done

with them.

There are sets of data where the variations in

methodology used are so large that the results of different

studies are not comparable. There are also studies reporting

dependent measures in ways that defy transformations to a common

scale. Examples of the latter are difference scores and ratios

of different kinds expressed without information about the

reference used so that they cannot be recalculated to original

data. In such cases, it may be possible to make the studies

comparable by using relative measures. Examples of this may be

found in Teichner and Whitehead (1971) which examined the effects

of massed and distributed practice on human learning, the effects

of noise on performance and the effects of feedback on tracking

performance. These analyses, performed as demonstrations or

exercises, represented a very early attempt at data base use.

However, they also illustrate the use of relative measures (e.g.,

percent difference between experimental and control groups) as a means for answering scientific questions.

Teichner 's work serves to make clear several important

points about the evaluation and subsequent, use of ergonomic data

in a comprehensive data base. First, critical evaluation of data

from the human sciences, while a difficult and perhaps tedious

chore, can be productively accomplished. Second, critical

evaluation and compilation of data in any .subject matter area

require intimate knowledge of the subject matter in order to

appropriately define the criteria for selection of data to be

accepted for inclusion in the data base. Finally, evaluation and

compilation consist not of simple mechanical manipulation of

abstract pieces of data, but require the full creative efforts of

dedicated scientists. Lide and Rossmassler (1973, p. 135)

perhaps best summarize the importance of these considerations

when they note, with the help of Lord Rayleigh:

"Critical data evaluation is a tedious and

exacting job that lacks the glamour of

research but requires many of the same

intellectual attributes. The participation

of experienced research scientists is

essential to the success of any compilation

effort, and our system of credits and rewards

should reflect the value of such contributions

to the progress of the profession. As

Lord Rayleigh remarked about the work of one

of his contemporaries

'Some may think that the same talents

and industry would be better devoted

to original work; but it must be

allowed that to elucidate and render

accessible the labours of others may

be a service as valuable as the

addition of new material to the

common store ' .

47

5. NATIONAL ERGONOMICS SURVEY

The SERDS concept encompasses two major categories of

data: anthropometric (human body) and behavioral (human

response) measurements. Both data categories are required by

private industry, government and the research community. However,

data available in the literature, are often out-of-date and, more

importantly, not statistically representative of the civilian,

American population. It is proposed that a National Ergonomics

Survey be conducted to obtain such measurements on a representative sample of the U.S. population.

The National Ergonomics Survey will initially emphasize

the collection of anthropometric measurements (SERDS Data Module

I) for several reasons. First, such measurements appear to be

more urgently needed by several industrial sectors than most

behavioral measures. Second, once anthropometric data are

obtained they are somewhat easier to organize, process and

disseminate than behavioral data. Third, the technology used to

obtain precise, accurate anthropometric measurements presents

challenging, special problems including: definition of

measurements, use and standardization of instrumentation and

standardization of procedures for data collection. Planning for

the development of several behavioral data modules is presently

under way. „ , Objectives and Requirements

Given the anthropometric surveys that have been made of

selected population samples for a variety of purposes by Federal

agencies and private companies, one can question the need for a

national survey considering the cost and other problems

associated with its conduct. Unfortunately, anthropometric data

generated in previous studies suffer from one or more of the

following limitations (Steinberg, 1974):

1. The data were from select segments of the

population and therefore have only limited

generality;

2. The data do not include all or even most of

the requisite measurements applicable to all

potential users;

3. The data in many instances are obsolete and

therefore not representative of the presentday U.S. population; and

49
4. The methods used to obtain data and the

conditions under which they were obtained

are often suspect or ill-defined.

These drawbacks may be attributable to two factors. First,

no single agency or organization has been assigned or assumed the

task of developing a comprehensive, anthropometric data base.

Second, the collection and analysis of anthropometric data

representative of the U.S. population is a costly, time-consuming

and exacting task, requiring the establishment of a planned,

structured and comprehensive program.

The only apparent alternative to making use of existing but

obsolete data, rules of thumb and trial-and-error is to conduct a national survey of a sample representative of the U.S.

population. The objective of such a survey would be in part to

collect anthropometric data that will be useful to a large number

of potential users. To meet this objective, a survey must

satisfy the following basic requirements:

1. The survey sample must be statistically

representative of the U.S. population with respect to age,

sex, ethnic origin, socioeconomic, and other demographic

factors;

2. Measurement methodology, instrumentation and

procedures must be standardized;

3. Data capture, storage, retrieval and

analysis must be computerized to permit the original, raw

data to be manipulated in many ways;

4. Computerized data must conform to the data

needs of potential users; and

5. The costs of instrumentation, data

collection, processing and dissemination must be acceptable.

State-of-the-Art of Anthropometric Measurement —Historical

Perspective ' ~

Following World War II, emphasis on fitting the machine to

man became critical for the performance and economy of high performance jet aircraft and even more so for spacecraft. As

human engineers and anthropometrists attempted to obtain 'more

accurate and precise data, many different methods for capturing data were devised. These new methods were designed to have the characteristics of (1) rapid data capture, (2) the capture of

50
data for unanticipated future use and (3) permanent data storage.

As a result, the current state of anthropometric measurement is

one of transition from a manual method, using well-trained teams

and "classical" anthropometric instruments (i.e. anthropometers

calipers, and steel tapes), to semi-automated and automated

methods which involve the use of computers and photographic

equipment. Some of these methods are designed to yield

additional information on body contours, surface areas and body

volumes as well as single, linear body measurements. Proponents

of some of the methods such as stereophotogrammetry (Herron,

1972) claim exceedingly accurate measurements; other

investigators raise questions about the effects of such factors

as time since last meal, respiration and subject motivation for

even the most sophisticated instrumentation techniques. Since

different investigators use different methodologies, questions

also arise concerning the comparability of data derived from

these different methodologies. This underscores the importance

of defining and standardizing anthropometric

measurement

Recent Trends in Anthropometric Measurement

Starting with WWII two trends in anthropometric measurement

have emerged. The first trend is associated with the need for

sizdng data and clothing tariffs for wearing apparel. The need

for sizing data determines what measurements must be taken. The

methodology used is manual because a number of measurements must

be referenced to underlying bone processes that can be detected

by only a manual approach. The most extensive compilations of

such anthropometric data have been produced by the U.S.A.F.

Aerospace J-ledical Research Laboratory at Wright-Patterson AFB,

Ohio and the U.S. Army Quartermaster R&D Command at Natick,

Massachusetts

The second trend is related to the human engineering of the

man-machine interface. Work in this area frequently involves

dynamic anthropometry, biomechanics, physiology and psychology.

The relationships among these disciplines are so closely

interwoven that it is difficult to draw sharp demarcation lines

among them. One of the distinctive aspects of this trend is the

necessity to establish spatial relationships in three-dimensions,

such as defining reach envelopes in the sitting position or the

location of parts- of the body in notion with respect to equipment

or instruments. The addition of the third dimension requires

sophisticated instrumentation.

Since 1960, the number of studies associated with both of

these trends has greatly increased. These studies may be

characterized as involving a relatively small number of subjects

but a large number of complex measurements. The instrumentation

51
used is state-of-the-art and expensive. However, some of the

methodologies employed, such as stereophotogrammetry and

ultrasonics, may ultimately replace the classical and manual form

of data capture, especially when the data capture methodologies

can be tied in with data computerization. This will eventually

permit the determination and evaluation of relationships that

could not previously be accomplished.

Today the U.S. defense establishment maintains and

periodically updates the largest compilation of male and female

anthropometric data. However, the applicability of this data is

strictly limited by the unique age and physical characteristics

distributions within the military services.

In contrast to the long history of military anthropometry,

which dates back to the Roman legions, civilian anthropometry is

virtually nonexistent. There are two reasons: (1) there has

been no single, central agency responsible for delineating data

needs and conducting data capture and (2) there has been no

clearly-delineated and organized group of data users willing to

sponsor and pay for data capture. As a consequence, different

organizations have collected their own data according to their

individual needs with only little regard to their potential for

reuse

.

Only one national survey of the U.S. civilian population has

been conducted to collect data on a sufficient number of body

dimensions of value to such data users as the wearing apparel and

mail order industries. The results of this survey, published by

the U.S. Department of Agriculture in 1941, covered women and

children (white only) living (or visiting) in seven states and

the District of Columbia (Obrien, Gershick et al., 1941; Obrien

and Shelton, 1941) . The objective of the study was to collect

anthropometric data useful for garment and pattern construction.

In point of fact, these data were used by NBS in developing

sizing standards for women's and children's clothes. Although

the data sample was not truly representative of the female/child

population, they were the only available data based on a large

sample size.

The National Center for Health Statistics (DHEW) initiated

its Health Examination Survey (one of three programs of the

National Health Survey) in 1959. The first cycle of this survey

(1959-1962) was limited to civilian adults living outside of

institutions. Its purpose was to determine the prevalence of

certain chronic diseases; the status of auditory and visual

acuity; the level of dental health; and 19 body size measurements

thought to be the most widely used. The second cycle (1963-1965)

52
involved selection and examination of a probability sample of

noninstitutionalized children aged 5-11 years. Its purpose was

to define the normal pattern of growth and development of

children in the United States. The third cycle (1971-1973)

involved children aged 12-17 years. The sample sizes were 6672,

7119 and 6768, respectively for the three cycles.

The DHEW surveys are conducted decennially and make use of a nationwide probability sample. This approach makes it possible

to obtain the desired information in such a manner that the

reliability of the results is determinable. This, together with

the fact that the measurements are standardized and controlled,

permits generalization of survey results to the entire U.S.

population. Further, when conducted decennially, the health

survey permits body changes to be detected over time due to

changes in nutrition level, life style and other factors and

allows trends to be discerned and used as a basis for meeting

future requirements. Thus, the DHEW surveys meet approved

standards of scientific rigor and provide the best statistical,

anthropometric data on the U.S. civilian population that exists

today. Unfortunately, because the survey's objective is to

obtain health, growth and nutritional data, the number of body

measurements taken is too restricted for use in other areas.

The number of individual growth studies that has been

conducted, usually involving a limited number of body

measurements, is very large (Krogman, 1941; Snyder, Spencer et

al., 1973). These studies involve students from grade school

through college. However, the utility of these data is low

because of a lack of comparability from study to study.

The remaining civilian, anthropometric data of interest come

from studies which are also based on specialized populations.

Some of the major studies have covered industrial workers, bus

and truck drivers, airline stewardesses, air traffic control

trainees and law enforcement officers (Cathcort, Hughes et al .

1935; Martin, Sabeh et al., 1975; Stoudt, Crowley et al . , 1970;

Damon and McFarland, 1955; Snow and Snyder, 196 5; Snow and

Reynolds, 1975). Although these studies were often wellcontrolled, the populations surveyed are too specialized to

permit generalization to the U.S. civilian population. In

summary, there is no anthropometric data base representative of

the U.S. Civilian population that contains enough body

measurements to have utility for most potential data users. The

following sections briefly describe alternative techniques and

instrumentation that appear to be applicable to a nationwide

anthropometric survey.

53
Classical or Manual Anthropometer

The classical anthropometer developed by physical

anthropologists employs a set of manual measurement devices

consisting of vertical and transverse linear scales, sliding

inside and outside calipers, spreading calipers, steel measuring

tapes, skinfold calipers and other specialized instruments.

These instruments are graduated in millimeters, with the caliper

verniers reading to 0.1 mm. In using these instruments, critical

body reference points are "marked" on the body surface or on a body stocking. These markings, based on the underlying body

structure, must be made by a skilled person to maintain

comparability of measurement across subjects.

The chief advantage of the classical anthropometer is that it

is a standard, off-the-shelf item. Such instruments are hand

portable and can be used in practically any kind of environment

to take almost all desired external linear body measurements. In

the hands of a trained survey team, the data captured using the

classical anthropometer would be comparable across different

surveys

.

One major disadvantage of the classical anthropom.eter is

that, since manual procedures are required, use of the

anthropometer is subject to human error and variability. Human

error can occur in scale reading due to parallax problems, manual

recording of data and transcribing data to permanent storage.

Human variability may exist when measurement involves a subjective element, such as taking measurements with a given

force required to compress body tissue. Human variability is

also represented in the people being measured when, for example,

one subject may have eaten a large breakfast while another has

had none. The negative effect of such artifacts can be reduced,

however, by (1) proper training of survey teams, (2) taking the

mean of several independent readings, and (3) requiring that more

than one person take the same reading. Also, since classical

anthropometry involves manual procedures, it is relatively time

consuming

.

A second disadvantage of the manual anthropometer is that its

use involves physical body contact. In a nationwide survey this

would require the use of both male and female team members, thus

making the survey effort labor-intensive. A third disadvantage

is that unanticipated measurements can never be obtained after a subject has been measured unless the same subject is measured

again. For example, if shoe manufacturers determine, after

survey completion, that a new foot dimension is needed, a new

54
survey would have to be conducted. Thus, present and future data

needs must be fully anticipated before survey implementation.

Although the instrumentation costs of manual anthropometry

are low compared to other techniques, the rate of data capture is

also relatively low. This increases the time required to obtain

needed data and raises labor costs. Since such instrumentation

is highly portable and compact, survey members may move from site

to site by car rather than in special vans required by other,

more bulky equipment.

Automated Anthropometer

The automated anthropometer is basically the same as the

classical anthropometer. However, data transducers, employing

commercially available sensors and linear encoders, are added to

permit data to be captured and read directly into computer

storage. Precision of the linear encoders is greater than 0.1

mm. Using a portable minicomputer, data can be captured and

stored on computer tape in real time. Various procedures can be

implemented for permanent storage and data transport. At the end

of each survey day, data can be transferred to a central computer

via commercial data link.

In addition to automatic data sensing and readout, some

instruments are equipped with pressure-sensing devices. These

devices reduce survey team member variability (both within and

between) in making measurements involving skin and hair

compression and increase the comparability of data across

subjects. Thus, the chief advantage of the automated

anthropometer is a reduction in human error and variability.

Automation also increases the speed with which readings o£

measurements can be taken, thus reducing labor cost and total

survey time

One potential disadvantage of automated anthropometer s is

that their bulk requires transport in a vehicle larger than the

typical automobile, i.e., a large station wagon or van. However,

a van does offer several advantages. It would be large enough to

accommodate behavioral as well as anthropometric measurement

equipment, a small portable computer for data storage, and

facilities for survey team work and rest. The van itself may be

used as the measurement environment as it is moved from site to

site or be designed to permit equipment to be moved easily from

the van to a nearby measurement site such as a school,

fairground, park or place of business.

55
Single Camera Photography

The techniques described above produce independent body

measurements. On the other hand, a photograph shows each body

dimension precisely located with respect to every other dimension

and also provides a record that can be retrieved for use m

capturing unanticipated measurements.

Single cameras have been used m conjunction with a background grid, or a grid may be superimposed on the image for

measuring major body parts (Dupertuis and Tanner 1950). However,

this procedure introduces a parallax error, except when the

distance between subject and camera is so large that the error

becomes negligible. Correction for parallax can be made

analytically, optically or physically.

One of the most sophisticated and expensive single cam.era

techniques is the "Photo-Metric" system (Hunt and Giles, 1956).

This system uses a combination of fixed mirrors, synchronized

electronic flash units and a precision camera. A relatively long

effective distance between camera and subject within a relatively

small space is possible with this configuration. A precise

arrangement of mirrors yields complete front, side, rear and

overhead views of a standing subject. All views are exposed at

once. Measurements, taken manually from the photographic images

with graduated scales, have an error of approximately 0.1%. This

method can be used with nude, marked subjects or with subjects

clad in a body stocking.

Variants of the single camera system include the use of highspeed photography and videotape. The distance from camera to

subject IS constant, with the subject turning for front, side or

rear views or, at short distances, portions thereof. Subject

movements are not critical during high speed filming. Data

capture is performed at a later date using a special ground glass

projection screen, light or sonic pen and computer. This process

is accomplished by projecting each film image on a screen, fram.e

by frame. Behind the screen, the operator touches the pen to

three points, namely: null, one end of dimension, and the other

end. The computer, using a conversion algorithm, computes each

distance. Since any number of frames may be used for one

dimension, the computer sums and averages all measurements for a given dimension with the average being entered into permanent

storage. This procedure averages out some, but not all, human

error, thus permitting the use of relatively unskilled labor.

56
The main advantage of single camera photography is that it is

a fast and efficient means of making a permanent record in the

field. There are several other advantages of photography. No

body contact is required. A body stocking does not distort

measurements. Field personnel requirements are low. Finally,

measurement does not fatigue the subject.

The Photo-Metric system is bulky, difficult to set up and

expensive. However, it can be installed in a large van and

checked out by skilled personnel prior to use, with only the care

of the camera and the positioning of the subject left up to the

survey team. Since front, side, rear and overhead views are

taken simultaneously on one film, the procedure is relatively

fast and efficient, and images are easily stored.

Single camera photography, and all other photographic methods

for data capture, have two major disadvantages: they do not

capture the third dimension and do not take into account the

compressibility of soft body tissue. Volumetric body

measurements cannot be obtained directly, unless circumferences

and girths are measured manually. In addxt-ion, some

measurements, such as finger length, are better made manually.

Fine details of the face and extremities require close-up (or

portrait type) photographs. The insensitivity of photographic

recordings to the compressibility of the body is a problem,

particularly for children whose waist circumferences and other

measures are sensitive to the compression of body tissue. No

existing camera recording technique appears to solve this problem

effectively.

One minor disadvantage of photography is that data capture

from photographic images is time consuir^ing and laborious. More

importantly, it is so fatiguing that human error poses a problem.

A light/sonic pen/computer combination may help alleviate this

problem. It should also be noted that (1) film processing must

be done very carefully to assure that the paper is not stretched,

(2) photographs must be stored in an environment where the

temperature and humidity are fairly constant, and (3) if

participants are photographed in the nude, the files must be

secured to prevent unauthorized access.

Instrumentation costs for a good single camera system are a function of the degree of sophistication and accuracy required.

For example, it is estimated that two partial mirrors could be

set-up in vans for about $200K, including pilot study validation.

Four photographs per subject would be taken representing the

obverse and reverse of the x-y plane, the x-z plane and the y-z

plane. Photographs of extremities and face would be made

57
separately. This system could also be used in conjunction with

the classical anthropometer s , where the single camera system

would provide back-up information and permit capturing unplanned

measurements later on.

Photogrammetry

Historically, photogrammetry has been used to survey and

measure the earth's surface from aerial cameras to develop

various types of contour maps. In anthropometry, this technique

consists of taking simultaneous photographs from two or three

cameras located on mutually orthogonal axes at preciselydetermined distances from a given, arbitrarily-defined origin.

In the Andrometric Camera System (Chaffee, 1961), the

subject's body is marked for specific measurements and then

placed at an arbitrary Cartesian coordinate origin. Working from

negatives, measurements between marked parts are taken and

converted to true scale values using a series of trigonometric

equations. Direct measurements can also riade using a calibrated film reader or oscillographic reader.

Perhaps the best but most costly photogrammetric technique is

an adaption of the stereophotogrammetric method used in aerial

contour mapping (Hertzberg, Dupertuis , et al . , 1957). A pair of

aerial cameras (e.g., AF K-17s) is mounted approximately 5 feet

apart and 12 feet from a subject to optimize the stereoscopic

effect of simultaneous pairs of photographs. In one version, the

photographic negatives are converted to a diapositive for use

with a Kelsh plotter. The Kelsh plotter is used to plot equal

dimension contours for each 90" rotation of the subject.

Profiles, surface arcs and circumferences define the shape of the

subject with an accuracy greater than the living body. That is,

the error of measurement is less than the contour changes due to

breathing and body movements. A less expensive plotting

technique involves the use of twin projectors: one red-lighted

and one blue-lighted. A white "flying spot" is used to identify

equal height contours. An analog-to-digital (A/D) converter and

minicomputer capture and convert the information to dimensional

data. However, since the operator must wear red and blues lenses

to achieve fusion of the stereopairs, only skilled and welltrained technicians can be used for data capture.

The Biostereogram technique, promulgated by R.E. Herron

(Herron, 1972), employs a variation of the flying spot plotter.

Algorithms, based on analytic geometry, are used to convert

imagery information to body measurements, surface areas and

contour characteristics, and body part volumes. Under precise

53
conditions,, stereophotos , holograms, X-rays, infrared rays, or

other forms of imagery provide a means of measuring organic forms

in three dimensions. Changes in form, as in movement or growth,

can be determined using time as a fourth dimension. Thus the

body can be characterized digitally, using Cartesian or other

coordinate systems, or analytically using contour maps, crosssections or physical replicas. Because of the accuracy and great

wealth of data obtainable, stereophotogrammetry has been used in

such fields as orthodontics, orthopedics, plastic surgery (facial

restoration) , prosthetic design, body and limb plethysmography

and tumor detection and growth.

The chief advantages of stereophotogrammetry over single

camera techniques are its smaller error of measurement and its

greater information content, particularly with respect to the

third and fourth dimensions. It is particularly useful when

contour and volumetric data are desired. Space and set-up

requirements are somewhat less than other methods and hence such

equipment is relatively more portable. Like all photography, it

is noncontact, does not tire subject or experimenter, and

provides a permanent record for later data capture.

Although the field equipment is relatively inexpensive,

central data capture equipment is expensive and . labor intensive.

Data capture also is laborious, time-consiaming and requires a high skill level. Since this technique is based on man's

natural, visual characteristics, the skilled technician must be

able to fuse two slightly different images into a single image

having three dimensions and have good depth perception to detect

surfaces with the same dimension. Because the nude, human body

is essentially monochromatic. Moire fringe patterns may be added

to increase contrasts between body points. Automating data

capture may be difficult because both fusion and depth perception

take place, not at the receptor level, but at a higher cognitive

level, thereby necessitating a man in the system.

A minor disadvantage of this technique is the requirement of

a dedicated computer and computer programs to reduce image

information to a desired digital or analog form. These programs

are based on the principles of trigonometry, analytical geometry

or fast Fourier transforms.

A single study to capture clothing-type data by

Biostereometry cost $150K for 30 subjects, or a per subject cost

of $5K (R. White, U.S. Army Natick Lab, Massachusetts). This

approach is obviously too costly to be used in a nationwide

anthropometric survey. Other techniques such as x-rays.

59
ultrasonics/ laser and holographic interferometry appear to have

potential use for a national anthropometric survey.

Advanced Technology

A number of advanced techniques have been explored on a preliminary basis as means of obtaining gross body dimensions

automatically, i.e., without a human observer in the loop. The

techniques included: optical/electro-optics, ultrasonics,

infrared. X-rays, lasers, masers and holographic interferometry

.

With all these techniques, the x and y coordinates from an

arbitrarily defined origin, whether Cartesian or other coordinate

system, are determined by an electromechanical sensor. The types

of sensors used range from linear optical encoders to a horizontal array of signal transducers which are swept

sequentially. These sensors generally have high accuracy.

Basically, all these techniques ds^termine the z coordinate in

the same general way. Critical dimension points are marked on

the subject and appropriate reflectors placad at these points. A

collimated beam of energy is reflected off the subject and

received by an appropriate transmit/receive device (TR)

.

Distance between the subject and the TR device can be calculated

from the time differential between the T and the R signals. The

time differentials are then used to define the unique, threedimensional characteristics of the human body.

Currently, a considerable amount of biomedical research on

internal body organs (including tumors) is being performed using

ultrasonics. Ultrasonics may have considerable potential as a fast, efficient and cost-effective technique for use in

anthroDometry . One version of the 'use of ultrasonics would

employ a large diameter annulus of two to three meters on which

signal transducers are located every 30°. Lateral resolution is

determined from the transducer spacings. However, in the case of

a single, traversing transducer, resolution could be obtained

from the beam width of the acoustic pulse. Vertical resolution

can be obtained from a radial optical encoder located on the

annulus' tilt axis. Transverse resolution would be determined by

acoustic travel time and have an accuracy equivalent to an

acoustic wavelength. Because the travel time for ultrasonics is

long, compared to electromagnetic energy, the determination of

the time differential between the T and R signals requires less

sophisticated equipment than would be required for other

techniques

,

The main advantage of these automated techniques is the speed

of data capture. Digitizing the three-dimensional coordinates

results in a data base that is versatile, parsimonious and

60
compatible with the digital computer. Data capture and storage

occurs in real time in the field. Later data retrieval,

compilation or analysis can be performed relatively easily.

Thus, the cost of human labor becomes minimal.

Like most state-of-the-art technologies, an R & D effort is

required to go from the theoretically possible to the practically

useful. Some of the problems that would be encountered are:

synchronizing the z coordinate to its appropriate x and y

coordinates, establishing the practical accuracy of the z coordinate, determining the measurements that can be made and

their accuracy, determining the error introduced by the participant's

positioning and movement and determining the error associated

with the reflectors. Theoretically, these systems should be

precise but practically they may not be as accurate as

anticipated.

Depending on the number of people surveyed and the number of

measurements taken, the cost per subject, including the R&D

cost, may be the lowest for all the techniques available for a nationwide survey, particularly when the data base may have to be

updated decennially.

Need for Technology Improvement

Historically, three international conferences have been held

to achieve standardization in the field of anthropometric

measurement. Today, with the increase in the number of

measurements taken and the requirements of increased accuracy, a need remains to further up-date, improve and standardize the

state-of-the-art in anthropometry.

The first area requiring up-dating and standardization is

terminology, i.e., there is a need for more precise definitions.

For static anthropometry, there is a need to incorporate such

concepts as skin/hair compressibility, attitudinal states of the

subject and time since last meal into the measurement

definitions. The problem is to provide definitions which are

independent of the technology or procedures used so that data

obtained by contact measurement are comparable to the data

obtained by noncontact measurement.

The second area of anthropometry which needs up-daring,

improvement and standardization is measurement instrumentation

and the procedures used. Research is needed to determine the

comparability of results when the same measurements are taken

with different techniques.

61
For a national survey, technology development and improvement

is required in three areas: fast, efficient and cost-effective

data capture and storage, the removal or reduction of the role of

the human in the data chain and, finally, a reduction in space

requirements to enhance the portability of the survey equipment.

The latter may be achieved when the others are realized.

For the short term, technology development should begin with

the automation of the classical anthropometer and its

accessories. The University of Michigan, in a recent

anthropometric survey of children for the Consumer Product Safety

Commission, has developed the most extensive, systematic

automation of the classical anthropometer to-date (Snyder,

Spencer et al . , 1975). Basically, the system involves modifying

each instrument to incorporate a pressure sensing device and a length measuring device, such as a 10-turn potentiometer, coupled

to the instrument blade by a pulley and cable system. . Electrical

readouts, activated by a push-button switch, are inputted to a minicomputer via a 12-bit, A/D converter. Two digital readout

meters provide visual feedback for pressure control and

measurement check. A keyboard/TV monitor provides input to the

computer for other data, e.g., participant name, age and sex. A

processor program completes the system; the systemi is easily

portable in a small van.

For the long term, technology development should concentrate

on the R & D of ultrasonics as a technique for large scale

surveys involving major body dimensions. The major justification

for an R & D program in ultrasonics is that it is currently being

investigated as a potential tool in biomedical research. If, for

example, ultrasonics can quickly and cheaply detect cancerous

tumors, then it might be possible to combine a health survey with

an anthropometric survey

.

Proposed Survey Approach

Objectives

Data collected in any survey must be generalizable , with a

reasonable degree of precision, to a clearly defined population.

If the data include biases or threats to external validity, then

the conclusions drawn will be ambiguous (Campbell, 1963). Biases

that preclude desired generalization may originate from

inaccurate measuring devices, the lack of standardized

measurement procedures and biases that derive from the selection

of participants. The latter are discussed in the following

sections of this chapter.

62
In addition to the effects of biases that create a constant difference in sample values from the true population

value, there are random departures in the sample values that are

due to the fact that only a part of the total population is

included in the survey. The precision of the sample data is a measure of how close these data are to the true population value.

A primary measure of the adequacy of any survey is the precision

of its findings. Precision, in turn, is a function of the

variability of the population being studied and the number of

participants in the survey. The number of participants is

usually determined by the funds available for the survey and the

manner in which such funds are allocated. Thus, the objective of

a well-designed survey is to avoid, where possible, biases in

participant selection and to obtain, for the amount of funding

available, useful data as precise as their potential users

require for a range of applications.

Criteria for Participant Selection

An unbiased selection of participants from a population

can occur only if each member in the population has the potential

of being selected with a calculable (and non-zero) probability.

The most common version of this criterion in survey design is one

that requires each member of the population to have an equal

chance of being selected (Moser and Kalton, 1958)

The criterion that each member of the population must

have an equal chance of being selected applies only in a design

in which the total population is sampled without any further

differentiation (stratification) . Major revisions to this design

occur when the population is stratified according to properties

of its members such as age, sex, income and education attainment,

or the members are grouped in clusters for sampling purposes

according to geographical proximity. The advantages and losses

that occur when these classifications are made are discussed

below. The equal probability criterion should be maintained,

however, for the subpopulations contained within each stratx^m.

Clustering generally prevents the equal probability

criterion from being applied since only individuals in specific

locales are surveyed. A measure of how restrictive clustering

can be is provided by a measure of the similarity of the

residents within the cluster. If the similarity is substantial,

then cluster sizes will have to be reduced and the number of

clusters visited increased.

63
Procedures for Selecting Individuals for the Anthropometric

Survey

The method of choosing participants for a survey may be

grouped into the following classes:

• "Judgement" or convenience sampling;

• Use of all or some fraction of the

individuals who have voluntarily entered

into some predetermined, geographicallydefined area such as a shopping center,

museum, fair and physician's office; and

e Random selection from a list of all members

of the population

.

The first procedure is employed in such applications as

market surveys where the weights of the sample stratifications

are adjusted to resemble the stratifications of the population.

However, the selection of individuals in the lowest level of the

design is not made at random but is rather based upon a fixed

feature—such as individuals conveniently available to the survey

team, or individuals who are aware of the existence of the survey

and have contracted with the survey team to participate.

Since convenience sampling does not meet the criterion of

equal probability sampling, convenience sampling can be

justified only if it can be^ demonstrated that there is little or

no variability in any particular sub-sample. This assumption is

usually made but there are few instances in which it is

empirically confirmed. Many texts have discouraged the use of

convenience sampling Closer and Kalton, 19 58)

.

Sampli-ng of participants who have voluntarily chosen to enter

an area in which the survey team has placed data recording

devices has increased in prominence with the current interest in

unobstrusive measurements (Webb, et al. 1966). Measurements can

be affected by a participant's "reaction" to the experimental or

survey situation. One of the most serious of these is the

knowledge that the participants are being compared with each

other. Reactions or measurements under these circumstances may

be sufficiently different from ordinary behavior to cast doubt on

the validity of the data. This criticism can be avoided by not

notifying participants of their involvement in the survey and

taking measurements in unguarded moments. Obviously this

approach is not feasible for an anthropometric study. In

addition, voluntary entrance into a prescribed area such as a

64
museum or shopping center may bias the sample. Museum attendees

may include a disproportionate number of school children and

their parents, whereas a sample of people at shopping centers may

be weighted with housewives and younger children.

The most common practice in obtaining survey participants is

to use a list of all individuals in the population and to extract

names from this list with either a systematic or random

procedure. A systematic procedure is generally discouraged—

especially if it can be shown that there is any periodicity

and/or grouping of names in the list on some relevant trait. If

the listing is complete, without errors and redundancies,

scimpling can be performed without bias by the use of tables of

random numbers. Participant lists which are free of

imperfections are rare for any large population, but reasonable

approximations do exist in such records as factory payrolls and

school attendance rosters. For a national survey, the best

approximation to a listing of the United States population is the

list of "segments" maintained by the Bureau of Census. These

segments are lists of households, rather than names. A single

segment usually consists of six adjacent households. Usually,

data are collected from all available members of a segment and

generalizations can be made only to this population and not,

strictly speaking, to all individuals in the United States.

However, if the Bureau of Census lists of segments were to be

used in a national anthropometric survey, the population to which

the results would apply would have to be revised to exclude two

major groups—those people who reside together in a non-family

relationship and residents of localities in which there have been

sizable population changes since the last census, as indicated

from other information sources

Use of More Complex Sampling Designs in Collecting Data for

a National Anthropometric Survey

The sampling plan described earlier for selecting

participants at random from a list of candidates is essentially a simple probability sample. Simple probability sampling is used

as a standard for other plans in which the basis of comparison is

the precision of the different plans. Simple probability samples

are also employed to collect data in pilot surveys.

Changing a sampling plan from a simple probability sample to

a more complex plan is usually done to increase the sample '

precision or for practical considerations in the collection of

data. A plan may also be designed to answer specific questions,

such as the difference between rural ^nd urban communities on a trait being studied.

65
Clustering in Sample Design

In surveys, clustering involves the designation of a geographically restricted area such as a city block, town or

group of homes. Some fixed percentage of available individuals

is sampled within the cluster. The proximity of the participants

in the cluster is its primary advantage. If vans are used to go

to selected locales to collect anthropometric data, then these

locales become the clusters in the sampling plan. Since the

residents in the area would be within an acceptable traveling

distance to and from the van, their appearance at the van for

measurement is made especially easy.

However, the most serious limitation of clustering is the

reduction in survey precision. The residents in a cluster may be

more similar to each other, in many respects, than they are to

individuals outside of the clusters. Individuals in a community

may be similar to each other in income, age, race and occupation

due to a tendency for individuals to group together on the basis

of these characteristics. This increased similarity may reduce

the "representativeness" of a cluster. To- avoid the biasing

effects of geographical proximity, the survey teara(s) will have

to collect a smaller amount of data from each cluster and include

more clusters in the survey design.

The effect of clustering on the variability of the total

sample is largely determined by the correlation between members

in the cluster. The sampling variance following clustering [Var

(C) ] is measured utilizing the following formula:

Formula 1 ; Var (C) = Var (R) [1 + (N - 1) p ]

;

Where Var (R) is the scimpling variance for a simple probability

sample of the same size as the clustered sample, N is the size of

each sampled cluster, and p is the correlation between members in

the cluster. This formula assumes that all N individuals in a cluster are measured.

Since ( p) is multipled by (N - 1) , the resultant effect of

increasing the variability of the results and reducing the

survey's precision is considerable. Cluster selection should be

guided by a principle of choosing those clusters which have as

much variability within them as possible.

66
stratification in Sample Design

The primary method for improving the precision of a simple

probability design is stratification. For example, to determine

the effects of ethnic background on body dimensions, the

population would be stratified using major ethnic categories--

including categories of mixed and indeterminate background and

then simple probability sampling would be performed within each

stratum. The requirements are that the strata be mutually

exclusive and that the categories encompass the total population

in the proper proportion.

Properties or characteristics for which stratification may be

desirable should form a continuum and thus a decision will have

to be made as to where to divide the continuum to form

categories. For example, if there is an interest in the effect

of income on anthropometric measurements, it might be desirable

to include representatives from low, middle and high incomes in

the survey. The ranges of income within a stratum would have to

be defined. Several techniques can be employed (Kesh, 1965);

their utility is measured by the homogeneity of the individuals

within each stratum as defined by the standard deviation. This

classification principle follows from the rule that the

subpopulation within a stratum, unlike the subpopulation within a

cluster, should be as uniform as possible.

If there is no basis for stratification, there would be no

reduction in the sampling error from that obtained with a simple

probability sample. The difference between the variance of a proportionate stratified sample and the variance of a simple

probability sample is approximately: — — 2

Formula 2 ; Var (X^pg) " Var (Xp^^Qp) Zn^ (u^ - y)

2

n

Where Xgpg is the mean of a simple probability sample, Xpj^Qp is

the mean of a proportionate stratified sample, is the

population mean in the ith stratum, y is the population mean, nj_

is the sample size in the ith stratum, and n is the total sample

size. The formula shows the importance of the difference between

the Uj^'s of the different strata on survey precision.

The proportion of the population within each stratum that is

sampled may be either uniform or varied. The former, generally

referred to as proportionate stratified sampling, will result if

the size of the sample from a stratum is made proportionate to

the size of the stratum with respect to the total population.

67
i

Optimum survey precision for the funds expende^ is

attained if the sampling fraction in each stratum In^I is directly

proportional to the standard deviation of each stratum and

inversely proportional to the square root of the cost per unit

sampled. The sampling fraction then becomes:

Formula 3 = k 1 n

.

N.

1

Where n^^ is the

^i is the

Si is the

^i is the

k is the

V^i

If cost and standard deviation are the same in all strata, the

optimum sample allocation is proportional ro the size of each

stratum.

If stratification is performed after the survey has been

conducted, the mean for the entire survey would be calculated by ' weighting the mean of each stratum by its proportion of the total

population so that the total survey sample mean (X) becomes

:

Formula 4: X = ZN. X.

N

Where is the obtained mean in the ith stratum and N is the

total population size.

The standard error of this mean is given by:

Where s. is the standard error of the mean of the ith stratum.

1

If a decision is made to proceed with the survey without

obtaining estimates of data variability or costs of collecting

data, then the final sample could be picked by simply selecting a uniform number from each stratum and weighting this result by the

proportion of the total population within a stratum. A more

frequently used approach is to utilize a uniform selection

fraction in each stratiim so that the probability of picking a

68
participant will increase with the size of the stratum relative

to the total population. This is known as PPS sampling

(Probability Proportional to Size) and is the sampling fraction

used in many current surveys

Selection of Strata

The previous section described advantages for stratification

in survey design; however, there are important limiting factors

in choosing strata. Strata will not be of any value if they do

not provide any improvement in survey precision. In addition,

they are of no value if they are based on factors for which there

are no available data.

The stratification factors should have some reasonable and

preferably known correlation with the variables being measured.

In a national anthropometric survey the utility of race, age and

sex categorizations could be justified due to their known

associations with body dimensions. On the other hand, years of

schooling, income level and occupation may have little or no

relationship to body dimensions.

Stratification for a national survey requires that data on

the entire population be available for each of the primary

sampling units (PSU) in which the stratifications are made.

Although data on each individual in a PSU are not likely to be

available in any data base, the Bureau of the Census does provide

statistical summaries of census tracts within Standard

Metropolitan Statistical Areas (SMSA) and counties. If the PSU's

are based on SMSA's and groups of adjacent counties, then these

data could be used to form strata consisting of census tracts

within the PSU's.

Some examples of properties for which stratification data are

available are

1. Percentage of the population in the tracts

that is under 18 years of age;

2. Percentage of the population in the tracts

that is over the age of 65;

3. Percentage of the population in the tracts

that is black;

4. Percentage of the population in the tracts

that is employed in blue collar occupations;

and

69
I

5. Median family income in each tract (Bureau

of Census , 1976)

.

Influence of Cost on Sample Design

As stated earlier, a primary consideration in survey design

is to obtain data with the maximum precision possible within the

resources available. An advantage of stratification is the fact

that it allows the survey designer to apportion the total number

of participants sampled in an optimal fashion, so that the number

in a stratum increases with the variability of data in the

stratum and declines as the cost of collecting data in the

stratum increases.

In addition to the direct costs of collecting data, it is

possible to distinguish two other sources which will reduce the

amount of funds available for data collection. These are

overhead or central costs, and moving expenses. The former

includes the expenses involved in training, managing, analyzing

data and operating a fixed site containing -he central office.

The latter includes the costs involved m locating, setting up

and maintaining the mobile vans in which the anthropometric data

may be collected. The travel costs will be affected by the

number and location of clusters proposed for the survey. The

number of clusters will be determined, in turn, by the similarity

of the participants in each cluster.

If the total budget is stable, then the amount and

geographical variety of data collected will be determined by the

overhead costs. If overhead costs remain fixed as well, travel

costs will be the limiting factor in the number of participants

who can be measured.

An approximation to the number of sampling locations and

participants can be made based upon the following cost

relationship (National Center for Health Statistics, 1972):

Formula 6 : B = + C^M + C^MN;

Where

:

B is the total survey budget;

C is the overhead cost;

o

is the cost associated with the establishment and

maintenance of a sampling location;

70
C2 is the cost associated with obtaining data from a participant at a sampling location;

M is the number of sampling locations*; and

N is the average number of persons measured at a sampling location.

The total number of participants sampled is given by:

Formula 7 ; n = M N;

Where n = total number of participants sampled.

A pilot study, may be conducted using simple probability

sampling to estimate C / C, and B is usually determined by

external factors. °

The optimum value of N is:

S

-yf^-^ Formula 8 : N (optimiam) = -^^ V ?r=- ^b ^2

Where S is the standard deviation of the population within a ^ PSU, and

S, is the standard deviation between PSU's.

b

Estimates of and can be obtained from a pilot

survey using the following formulas

? ^ (v> * _ p M ^ Formula 9 ; = E

^ i

' ; ^ = ^ M-1

Formula 10 : ^w ^ ? , _1 ^^i ' 1 = 1 n

Where nj_ is the number of persons measured in the ith sampling

location;

P| is the proportion of persons sampled in the ith sampling

location with the sample characteristic;

P' is the proportion of persons in the total sample with the

characteristic; and

q! = 1 - pr

* One sampling location is usually contained within each selected PSU

71
Once N (optimum) is found, the number of sampling locations

(M) can be derived from the following equation:

Formula 11

:

M (optimum) = B ~ C

o_\ ' N (optimum)

C + C ^1 ^2

Data on several characteristics of each person will be

measured and collected in the anthropometric survey. A decision . will have to be made on which characteristic ( s ) to use in the

above formulas. A conservative approach would be to base the

decision on the trait (s) which are the most variable. A more

practical approach would be to use a trait (or a composite of

traits) which is judged to be especially important for the

purpose of the survey

.

Effects of Nonavailability of Participants Selected for

the Survey

The previous section discussed several issues related to

obtaining the optimum number of sampling locations and

participants for an anthropometric survey. The lists of

participants would be derived from the lists of segments

maintained by the Bureau of Census. A survey design comparable

to the design used by the National Center for Health Statistics

is described in the following section.

Although lists of prospective participants can be designated,

the actual data collection will be for a smaller number than

originally planned. This may be due to one or more of the

following

:

• Errors in the original list. Many of the

errors are due to changes which make the

original list obsolete. An example may be

the listing or persons who are deceased or

have moved out of the area being surveyed;

• Individuals may reside at the address shown

in the list, but it may not be possible to

reach them, if their work requires them to

be away from their residence for long

periods; and

• Refusals by persons who are designated and

contacted to participate.

72
If these reductions in the survey size are small and are not

biased—i.e., all individuals in the population have an equal

chance of being omitted after being listed, then it will only be

necessary to make an adjustment to the data similar to a correction for empty cells in an analysis of variance. One

procedure is to employ a multiplier consisting of the number of

participants selected for a sample in a particular subcategory

divided by the number of participants from which data were

actually obtained. This value is then used to weight the

obtained data in each category (National Center for Health

Statistics, 1970)

A more serious problem with the nonavailability of subjects

is the bias that may be introduced. For example, individuals,

such as salesmen, whose occupations require that they travel

extensively, are less likely to be present during the period when

the van is at a sampling location. Similarly, certain groups

such as older women are more likely to refuse anthropometric

measurement than other groups

Biases occur, almost inevitably, in any survey and several

procedures have been adopted to deal with them. As a rule they

are only partly successful. These procedures include:

Redefining the original population . If the

lists from which potential participants are

selected are taken from the last decennial

census, then areas of substantial home

clearance activity cannot be used. This

might occur when offices and factories

replace private residences as the character

of a neighborhood changes . A common

practice in major surveys is to exclude

areas of large population change.

m- The number of individuals who are difficult

to reach may be reduced with repeated

contacts at random times. The form of the

contact sHould also be varied—telephone

calls, letters and personal visits. If vans

are used to collect data, they should be

made available to the participants during

weekend and evening hours

Payment of participants . This type of

incentive seems to be more effective than

any other inducement—such as a letter of

appreciation. The optimum amount of payment

73
for participation has not as yet been

studied. The National Center for Health

Statistics found that telling people that

they would receive $10.00 at completion has

a significant effect on reducing the

proportion of persons who refuse to

cooperate (National Center for Health

Statistics, 1975) . Proposed Survey Design

The survey plan can be defined in detail only as information

is made available related to those properties on which the sample

should be stratified. Data may be obtained in a pilot effort on

costs of establishing test facilities and collecting information

as well as the variability of participants within clusters and

stratum.

The design tentatively proposed is a multistage, stratified

sampling plan whose ultimate samping unit is a cluster of

adjacent households. These clusters are segments which are

located and defined on the basis of segment maps provided by the

Bureau of Census.

The survey would start with the use of TAB areas and Primary

Sampling Units (PSUs) . TAB areas divide the United States into

subuniverses of major geographical areas, such as the Middle

Atlantic States and all large, urban concentrations. Generally,

TAB areas are used for administrative purposes in organizing a survey and analyzing data.

The survey would use the PSU as the basic element or unit for

sampling. The United States has been divided into approximately

1900 PSU's, each of which consists of at least one or more

contiguous counties. Each PSU contains a population of at least

7 500 in the West and 10000 in the East. PSU maximum size is

around 2000 square miles in the West and 1500 square miles in the

East. In addition each Standard Metropolitian Area (SMA) is

considered a PSU.

The Census Bureau attempts to make each PSU as physically

compact and diverse in population as possible. Stratification of

the United States (or of the TAB areas) should be made on the

basis of the information available in Bureau of Census atlases.

Some parameters which may be useful for stratification include:

the proportion of the population that is non-white, population

density (to insure a representation of small, rural areas) and

percentage of labor force that is employed in blue collar

74
occupations. After stratification has been completed, the

selection of PSU ' s within each stratum should be made on a random

basis with a fixed selection ratio from PSU's which have been

adjusted so that their chance of selection increases with

population size.

The PSU's that are picked would then be divided into

Enumeration Districts of 500 - 1000 adjacent households. These

would then be sampled randomly with another fixed selection

ratio. Finally, the Ultimate Sampling Units (USU's) of

individual segments would be obtained on a random basis within

each Enumeration District with still another selection ratio.

All individuals within a segment would then be asked to take part

in the survey

The sampling ratios at the different levels of the plan would

be designed to produce a fixed number of PSU's and participants.

These totals are determined from the formulas for optimal

allocation of subjects and PSU's in a stratum after estimates are

made of both cost and population variability.

The National Health Survey conducted by the National Center

for Health Statistics uses an average selection ratio of 0.2 0 for

each TAB area in selecting a PSU for stratification. The

s.election ratio for picking segments within a PSU is kept at

0.0036 so that the probability that any particular segment in a

TAB area would be picked is 0.00072.

Problems Associated with a National Ergonomics Survey

Standardization of Terms and Measurement Techniques

Today, major problems in ergonomic measurement are

standardizing terminology and defining a measurement technique

for each dimension. In 1971, Garrett and others published "A

Collation of Anthropometry" in two volumes. According to the

authors, "This collation is a critical comparison of measuring

techniques and anthropometric data from 48 American and Foreign

sources. Approximately 2000 dimensions cover the anthropometry

from 16 countries ..." Several examples of a lack of

standardization across different studies may be noted in

examining this compilation of surveys.

For the term "Interscye," the following have been used:

Inter scye Breadth, Cross Back Width and Posterior Chest Width.

These words may imply different operations to different

investigators. Similarly, compare the two following operational

definitions of "Interpupillary Distance";

75
(1) "Measure the distance between the subject's

pupil centers. To do this, instruct him to

look at whichever eye you hold open. Rest

the sliding caliper lightly on his face,

close your right eye, and center the fixed

; top before his right eye. Now open your

right eye, close your left one, and center

the sliding tip before his left eye. Do not

allow his head, your head, or the caliper to

move during the measuring," and

(2) "Subject sits. After instructing him to

look at the point between the

anthropometrist ' s eyebrows, and with the bar

of the sliding caliper resting lightly on

the subject's face, measure the distance

between the centers of the subject's

pupils .

Needless to say these two definitions genera-ced different results

for Interpupillary distance. Thus, the question of data

comparability arises when studies are performed utilizing

different definitions (instructions)

.

Definitional and procedural problems such as these cannot be

handled without the development and adoption of voluntary

standards by the ergonomics community. Accordingly, Chapter 2

(System Concept) addressed voluntary standards development as one

of the principal functions of SERDS

.

Comparability of Measurement Techniques

A second problem is data comparability when data capture

involves different measurement techniques (instrumentation). Todate, no study has attempted to determine whether a number of

measurements taken on a large number of participants by different

measurement techniques yields equivalent data.

The types of measurements most likely to be affected by

different techniques are those involving skin compression of

soft-body tissue and those requiring a reference to prominent

skeletal landmarks. Since children have undeveloped skeletons

and proportionally more soft body tissue than adults, the problem

of nonequivalence of data across measurement techniques should be

greatest for children. Because of this problem, the use of

contact measurement techniques (i.e., an automated anthropometer

)

appears to be the only way of insuring data reliability and

accuracy.

76
Voluntary Participation

A third problem, unique to a nationwide survey of the

civilian population, is that of voluntary participation.

Although this was briefly touched on earlier, it deserves special

emphasis here. Unlike military populations, the adult, civilian

population is a "noncaptive audience." People may be motivated

but cannot be forced to participate in a survey. This may have

an effect on the degree to which the sample measured is actually

representative of the U.S. population as a whole. For example,

most adults will be at work during prime measurement time (8:00

am to 5:00 pm) . Some may consider their time too valuable to

volunteer. Certain groups may feel they are being used as guinea

pigs for the benefit of other groups and not themselves. Others

may have reservations about how and by whom data will be used.

Another problem associated with voluntary participation is

the failure of population extremes to be represented in a statistical distribution of body measurements. Examination of

data from two recent surveys of children conducted by the

University of Michigan and the National Center for Health

Statistics, DHEW, illustrates this artifact. The extremely

endomorphic (or obese) and ectomorphic (very thin) children fail

to show up in the results of these studies. Undoubtedly, one

cause of the lack of participation . by individuals that diverge

from the population mean is personal sensitivity. On the other

hand, the well-built, mesomorphic child, with positive feelings

regarding his or her physique, is more likely to volunteer. As a result, the distribution of obtained measurements will be more

peaked (leptokurtic) and have a smaller dispersion than the

theoretically normal population distribution.

Other classes of individuals are also likely to be

underrepresented in a general U.S. population survey. Included

are the handicapped, elderly, institutionalized individuals and

other persons unable or unwilling to volunteer for a measurement

survey. With these factors in mind, it must be accepted that

even the most carefully designed survey will produce only an

approximation of the "true" U.S. population.

It may be claimed that the omission of population extremes

will have only a negligible effect on the statistics of a sample

distribution since they represent only a small proportion of the

total population. However, unless the characteristics of the

"true" population can be identified, the proportion of the sample

distribution included by a process of self-selection is unknown.

In other words, experience and logic suggest that population

extremes do exist and must be taken into account when making

population estimates from survey data.

77
Raw Data Storage and Personal Privacy

The ideal plan for a national ergonomics survey would predict

all of the data required for all possible future applications.

Only the grouped measurements and measurement statistics that

satisfy these uses would be collected and retained. However, at

pres-ent there is no technique for making an estimate of the data

required for all foreseeable applications. Instead, it will be

necessary to collect and store all measurements taken on each

individual as raw data. Such storage would permit maximum

freedom in the use of raw data for unanticipated data

manipulations. For example, a manufacturer of shoes may require

a correlational matrix to be developed for foot-length to footwidth ratios for white males, above 20 years of age, residing in

an urban environment and earning an income of more than $20,0 00.

A data base containing raw foot measurement data could be used to

obtain the needed matrix; a data base using only grouped, rather

than individual data, could not.

However, a data base of raw results poses a problem in terms

of complying with the provisions of the Privacy Act. Therefore,

the development of approved safeguards against noncompliance is

essential to the acceptance and conduct of a national survey.

One proposed approach is that recommended by the U.S. Department

of Commerce (Fong, 1977) . This approach utilizes a Data Base

iManagement System consisting of two functions. The first

function is associated with data base input and assigns a random

number to represent each individual measured. The random number

assignment eliminates the individual identification that is

possible with a nonrandom sequence of number assignments.

Individual residence information is identified only in relation

to the Primary Sampling Units used.

The second Data Base Management System function prevents the

output of data in any other than grouped, summary statistical

form. This function is accomplished by system software. In

addition, compliance is also achieved due to restrictions placed

on the number of demographic stratifications that are employed.

In other words, individual identifiers —age, sex, and birth

date —will generate only relatively large groupings of data. In

this manner, successive elimination through multiple regroupings

could not be used as a basis to extract data on a single

individual or small group.

78
Sexual and Ethnic Sensitivity and Personal Privacy

Many citizens are sensitive on matters of sex and ethnicity.

These are natural concerns and must be respected. Sensititivity

to sex and age can be reduced by the proper mix and training of

individuals on the survey teams. For example, female team

members are used when women are being measured and male members

when males are measured. In certain regions of the country,

survey teams would include a member of each, well-represented

ethnic group. Individuals with prior teaching experience would

be on the teams that measure children. Teams would receive presurvey training on how to deal with these and other sensitivities

such as choice of words used to represent minority groups and on

how to treat participants who may be clad in body stockings for

the measurement process.

In summary, social, psychological as well as technological

issues must be carefully considered and satisfactorily resolved

before any plan to conduct a national survey can be implemented.

The acceptance encountered by survey researchers in recent years

for handling issues such as these suggests not only that these

matters can be satisfactorily resolved but that there is

precedent for the manner in which this should be done.

79

6. DATA PROCESSING AND OUTPUT

The purpose of SERDS is to facilitate the use of critically

evaluated data extracted from the published ergonomics literature

and from a national ergonomics survey of selected behavioral and

anthropometric characteristics of a representative sample of the

U.S. population.

All information and data considered for inclusion in SERDS

will be assigned to appropriate data analysis centers for

critical evaluation by subject matter specialists. General

criteria for the evaluation process will be developed by the

SERDS Office in conjunction with its Advisory Panel and User

Council (as indicated in Chapter 2, System Concept). Specific

criteria for critical evaluation are expected to vary from one

subject matter area to another; therefore, each data analysis

center will be guided by the general criteria but also will

develop more specific criteria to guide its evaluation

activities. Data and information that meet both sets of criteria

would become part of the SERDS data base.

Three forms of information processing will be undertaken by

SERDS:

• Scientific and editorial processing by data

analysis centers or individual subjectmatter specialists on a one-shot basis;

• Development of voluntary standards for

ergonomics research and measurement; and

• Computer editing, processing and file

updating of numerical data and narrative

text

It is anticipated that these forms of processing will meet a wide range of user needs and provide the housekeeping required to

maintain and manage the SERDS data base.

Scientific and Editorial Processing

The scientific and editorial processing and repackaging of

selected and evaluated source data and information may take one

or more of the following forms

• Preparation of critical reviews and surveys

on topics of current interest;

81
• Production of tables of selected numerical

data required routinely for ergonomics

applications by the scientific and technical

community; and

• Generation of selected, annotated

bibliographies, notes on standards

development activities and summaries of

current ergonomics research.

The above are basically intellectual activities which may or may

not require computer-assisted file searching, output formatting

and text generation.

Repackaged data and information from this activity will be

announced by means of scientific and technical journals,

specially prepared mail circulars or a user-oriented newsletter.

These products will be disseminated by the SERDS Office, data

analysis centers, the National Technical Information Service and

other means to help assure broad access and widespread use.

Two classes of users are anticipated: sustaining or

continuing users who pay a fixed fee to subscribe for a period of

service and nonmembers who pay on a service-by-service basis.

Sustaining member users of SERDS would be entitled to products

and services as part of an annual membership fee. Nonmember,

individual or institutional requestors would be charged fees for

these items at individual and group rates on a cost-recovery

basis. The output from SERDS should complement and supplement,

but not duplicate or compete with, other types of ergonomics

information and data offered for sale by scientific and technical

associations or the private sector.

Ergonomics Research Standards

As in other fields of science and technology that place a

premium on originality of research, there is a lack of

standardization in ergonomics research. Chapter 5 (National

Ergonomics Survey) illustrated several of the problems that arise

when a field has not yet achieved a satisfactory degree of

agreement on the way in which it undertakes research. These

include nonstandard terminology, measurement procedures,

nonmenclature and instrumentation, calibration methods, and data

recording, processing and reporting.

Although an excessive emphasis on standardization in these

and other areas can hamper the advances that normally occur in

science as new paradigms and practices are adopted, at no time

82
has ergonomics or its related human sciences been afflicted by

overstandardization. In fact, the single greatest obstacle to

the present-day use of ergonomics data can be attributed to the

lack of comparability of data caused by too little

standardization. Thus, while standardization must be approached

cautiously to avoid imposing undue restraints on the creative

research process, standardization is essential to promote the

growth and advancement of behavioral science.

Accordingly, it is envisioned that standards for ergonomics

research will be a major aspect of the SERBS program and a principal activity of the SERBS Office. Standards preparation

may take place based upon an initiating request from any

interested individual or group or be commissioned by the SERBS

Office to supplement its own activity.

Voluntary research standards will be disseminated widely to

encourage their adoption in future research. Potential users of

standards will include researchers, system planners and

educational institutions that give research courses in

ergonomics

Other standards-related efforts of SERBS would include:

coordination with national and international voluntary,

standards-setting organizations in the development of productspecific standards; cooperation with scientific and technical

associations in the development and promulgation of standards

review projects; and developmental support to Federal agencies in

their standards development programs.

Computer Processing and Output

Until more is known about the types and volume of literature

and data to be processed by SERBS, it is not possible to do more

than speculate on the hardware and software requirements of the

data processing system. Most, if not all, of the functions that

now appear to be called for —editing and file allocation,

statistical computation, modeling, updating and display—are

believed to fall well within the present state-of-the-art and can

be implemented with existing software packages.

The data processing services to be- performed by SERBS for its

users will include but not be limited to: • Combination of discrete sets of data;

» Computation of descriptive statistics;

83
• Development and use of behavioral and

biomechanical models and algorithms;

• Routine listings of raw data;

• Production of magnetic tapes for SERDS

users;

• Data base updating;

• Special search inquiry processing; and

• Remote terminal interfacing.

Again, products and services would be offered on a costrecovery basis. Magnetic tape records would be leased to users

at fees set to reflect the type, amount and frequency of updating

of data requested.

84
7. PRELIMINARY SERDS PROGRAM PLAN

The Program Plan that follows has been structured to

identify and meet the needs of commerce, industry, government

and the research community for a single, reliable and valid

source of ergonomics data. The goal of the plan is to provide

access to a limited set of data by FY 81, to a more comprehensive

data base beginning in FY 82, and to continuing development,

services and products thereafter.

The program plan consists of three major subplans

1. Plan for the Management and Operation of SERDS;

2. Plan for a National Ergonomics Survey; and

3. Plan for Critical Evaluation of Published

Ergonomics Data

Plan 1 is essential to the accomplishment of the other two.

Plans 2 and 3 are essentially independent and could be

implemented individually or in sequence if budgetary or other

factors do not permit simultaneous development. In this event,

however, users would not have access to all of the data that

would otherwise be available.

The three subplans are summarized in Tables 4, 5, and 6,

respectively. Each plan starts with a statement of the

objective, followed by a sequential listing of critical plan

milestones. In order to show the interrelations among the

plans, milestones from one plan which are in the critical path

of another plan appear in lower-case letters, without sequence

numbers. Horizontal lines designate the duration of each

milestone activity from one fiscal year and quarter to another.

Solid lines represent activities of a developmental, planning

and management nature; and dashed lines denote continuing

services or products to be provided by SERDS.

Plan 1 - Plan for Management and Operation of SERDS

Plan Objective : To provide a focal point for the orderly

planning, coordination, management and operation of a Standard

Ergonomics Reference Data System.

85
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1.1 Develop Preliminary SERDS Concept

The purpose of this effort, undertaken in FY 77, was to

conduct a preliminary qualitative assessment of potential user

needs for ergonomics reference data and develop a concept for

meeting these needs. That assessment and concept development

were reported earlier. It is envisioned that this preliminary

report will be distributed on a limited basis to potential users

early in FY 78 and will form the basis for a continuing dialog

and revision of the concept in succeeding years.

1.2 Conduct User Needs Survey

Activities associated with this milestone are aimed at the

development, pretest, administration and evaluation of a quantitative survey of user needs for ergonomics data. The

purpose of the survey is to obtain detailed information on

requirements for data, measurements, precision and accuracy of

measurement, and examples of specific applications and their

expected social and economic benefits. This information will be

used to define the scope of SERDS and establish priorities for

critical evaluation efforts and the characteristics to be sampled

in the national ergonomics survey.

The specific activities planned include:

1.2.1 Preparation of a detailed list of potential

data needs;

1.2.2 Development and pretest of a structured

interview/questionnaire and schedule for

assessing needs;

1.2.3 Completion of questionnaire by potential

users followed by in-depth interviews of

selected users; and

1.2.4 Reduction and analysis of questionnaire and

interview data.

It is anticipated that this milestone will be accomplished by the

end of FY 78.

1.3 Establish Data Priorities

The aim of this activity is to establish priorities for SERDS

data. These priorities will be illustrated by means of a master

table that summarizes and tabulates the frequency with which data

88
needs, independent of their intended applications, occur across

the spectrum of users surveyed. It is expected that this table

will reveal a high level of demand for selected anthropometric

and behavioral measurements not currently available in usable

form from the published literature and thereby permit the

isolation of the measurements required for the national

ergonomics survey.

1.4 Establish Provisional SERDS Program Office

An interim mechanism for the management of SERDS will be

required until a decision has been made regarding its ultimate,

permanent organizational home. This activity will lead to a recommendation to management for providing a temporary

organizational locus for SERDS within NBS . Alternatives to be

studied for such a provisional arrangement include: augmentation

of an existing section's/division's mission; formation of a new

organizational entity; and creation of a special interim office.

1.5 Establish Provisional Advisory Panel

For SERDS to be properly managed there must be reliable

feedback from the scientific and technical community. During the

pilot project the services of consultants and advice from

individuals attending the government and industry meetings served

this purpose. However, a more formal, stable arrangement will be

required if continuity and consensus of opinion are to be

achieved during the initial phases of SERDS development.

Therefore, it is planned that a Provisional, Ad Hoc Advisory

Panel be created for this purpose from a list of nominees

suggested by staff and approved by NBS management. This panel

would operate throughout the last-half of FY 7 9 and in FY 8 0 and

would convene at least twice during that period.

1.6 Establish Provisional User Council

Responsiveness of SERDS to its potential user community

requires that it have a forum for the continuing identification

of SERDS requirements and the uses to be made of the data base.

During the pilot project this was accomplished by means of

meetings and presentations to representatives of trade

associations, other government agencies and contacts with

specific industries. In the future a more formal and structured

basis for obtaining user input will be required. Therefore, a Provisional User Council will be formed from among those trade

associations and other organizations that have or will express an

interest in SERDS. Selection of representatives will occur

through self -nomination (followed by evaluation of credentials)

89
and invitation. The User Council would be formed in the secondhalf of FY 79 and meet at least once during FY 80.

1.7 Develop Staffing Plan for Permanent SERDS

Office

By the end of FY 79, it may be anticipated that SERDS

planning will have reached a stage at which it will be possible

to develop a staffing plan for a future, permanent SERDS office.

This plan will identify the skills, levels and number of staff

required to continue the management, coordination, planning and

operation of SERDS as a permanent data service. The plan will

also provide a basis for projecting the cost of the staff

component of the SERDS budget.

Because of the expected use of contractor and consulting

personnel on a temporary basis for various system development

tasks, it is not presently anticipated that a large staff would

be required for SERDS. However, a management and specialist core

staff of from four to seven persons may be required beginning in

FY 81.

1.8 Study Alternatives for Location of Permanent SERDS Office

In Chapter 2 (System Concept) several alternative sites for

the location of a permanent SERDS Office were discussed.

However, sufficient inforation was not available during the

pilot project to present a thorough and detailed analysis of

these alternatives. In FY 79 and 80 a study would be undertaken

for this purpose.

1.9 Establish Permanent SERDS Office

SERDS products and services will be offered to the user

community beginning in FY 81. At this time a permanent SERDS

Office will be required in order to provide users with the

assurance of system continuity and appropriate management. A

decision regarding the formation of a permanent office should be

made no later than the beginning of FY 81.

1.10 Acquire and Program Data Processing and

Analysis System

The aim of this activity is to develop specifications for the

procurement of computer time and programming for processing SERDS

data. Tasks associated with this activity will focus on the

design and application of a number of general-purpose, computer

programs for data storage, retrieval and analysis; file

90
manipulation; terminal access; and computer-assisted text

preparation, editing and printing. It is anticipated that these

efforts will benefit from close collaboration with the Data

Systems Design Group of the NBS National Standard Reference Data

System, the NBS Institute for Computer Sciences and Technology

and the NBS Office of Technical Publications. The planned data

processing and analysis will be capable of supporting the

requirements of the national ergonomics survey and the critical

analysis activities of SERDS Data Analysis Centers. Planning and

development will be initiated in the third quarter of FY 79, with

an operational processing system being targeted for the first

quarter of FY 81. Thereafter, it is expected that data

processing and analysis activities will continue in order to

develop additional modules for the source automation of technical

manuscripts, the statistical manipulation of data and the use of

man-system models.

1.11 Establish and Maintain Permanent Advisory

Panel

The goal of this activity, which is planned to coincide with

the formal establishment of SERDS, is to replace the interim

advisory panel with an enlarged and permanent advisory mechanism.

1.12 Establish and Maintain Permanent User

Council

It can be expected that a number of Federal agencies and

industries will choose to use SERDS on a continuing basis.

Therefore, a mechanism for permitting these users to have a voice

in SERDS planning and operations will be necessary to insure that

the system is responsive to user requirements. One possibility

is for users who wish to be represented on the Council to apply

for renewable term membership on the Council at an institutional

fee that will cover the cost of subscriptions to a selected

number of SERDS products and a designated level of data

processing service. The permanent council will replace the

Provisional, User Council beginning in FY 81.

1.13 Provide Continuing User Services and

Standards and Assess Impact of SERDS on

Users and Technology

Sound system design requires that a system have a means for

the periodic assessment of its effectiveness. In the case of

SERDS, "effectiveness" can be measured in terms of system use by

the scientific and technical community and the assessment of the

value of its products and services provided to its users.

91
Accordingly, this effort will involve the collection and periodic

reporting of usage and impact statistics. This evaluation

activity will begin in the third quarter of FY 81, six months

after the initiation of critical evaluation products and services

(See Table , Milestone 3.5).

If an objective impact assessment indicates that the SERDS

system is not being used or fails to meet the needs of its users,

operation of the system should then be terminated after

reasonable attempts to improve conditions have been exhausted.

However, if impact assessments are positive, it then follows that

SERDS should continue to provide products and services to the

user community.

One of the major elements in this continuing program of

service will be the development and support by SERDS of standards

for ergonomics measurement. Examples of the forms which this

service might take were described earlier in this report.

Suffice it to say here that standards for ergonomic science, as

for any other discipline, are essential to the creation of a

valid and credible body of knowledge and timely, cost-effective

application of that knowledge.

Plan 2 - Plan for a National Ergonomics Survey

Plan Objective ; To develop and provide a capability for user

access to selected ergonomics data representative of the U.S.

population.

2.1 Assess Alternative Measurement Technologies

Although many user needs for ergonomics data can be fulfilled

by access to critically-evaluated data extracted from the

published literature, existing published sources do not contain

accurate, up-to-date information and data in many ergonomic areas

for which there is a widespread technological need. Such areas

include: the measurement distributions of the static and dynamic

anthropometric characteristics of the human body and the sensory,

information processing and response characteristics of man as

such characteristics are represented in the U.S. population.

Existing literature, for example, does not contain an adequate

data base from which data can be obtained for use in sizing

clothing, personal protective devices/equipment, the arrangement

of workplaces or for the location and design of displays,

controls and informative labels. At present a large number of

devices exists for measuring and capturing such data. Chapter 5

(National Ergonomics Survey) discussed alternative anthropometric

measurement techniques that are now in use. A similar situation

92
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exists with respect to the measurement and capture of other

behavioral data such as the distribution of near- and far-point

visual acuity, minimum hearing thresholds, and the speed and

accuracy of response to signals of varying intensity, frequency,

duration and repetition rate. Without a comprehensive

examination of the many measurement devices or technologies that

might be used in a National Ergonomics Survey, it would be

impossible to select a cost-effective and technically adequate

mix of instruments for use in the national survey. Accordingly,

this effort is directed at evaluating alternative measurement

technologies with respect to cost, feasibility, precision and

accuracy. It is anticipated that this evaluation will begin in

the third quarter of FY 78 and be completed by the end of FY 79.

It would probably be performed under contract by a qualified

organization with a demonstrated capability in ergonomics

measurement and technology assessment.

2.2 Develop and Adopt Standards for Ergonomics

Survey Measurement

Although attempts have been made to standardize the process

of ergonomics measurement, a number of problems with respect to

the use of common units, measurement techniques and reporting

formats remain unresolved. Accordingly, it is proposed that an

attempt be made to achieve a consensus among ergonomics

specialists on the nomenclature, devices and practices to be used

in the national ergonomics survey. This activity will represent

the initiation of a continuing program aimed at promulgating

voluntary ergonomics research standards. It is scheduled for

completion at the end of the third quarter of FY 79. Activities

2.1 and 2.2 are critical to the accomplishment of all subsequent

milestones in this plan.

2.3 Procure Measurement Instrumentation, Data

Processing Equipment and Vans

Given the selection of a cost-effective mix of measurement

technologies and equipment and agreement on voluntary standards

for accomplishing measurement, the measurement equipment, field

data processors, and mobile vans for equipment transportation can

be specified and procured by either NBS or a contractor. This

phase would be completed by the end of FY 8 0 and allows time for

equipment development if suitable devices are not available offthe-shelf. It is anticipated that a minimum of four, fully

instrumented vans will be required for the survey.

95
2.4 Develop Survey Sampling Plan and Procedures

Chapter 5 of this report has focused on the conceptual

challenges to be met in developing and implementing a sampling

plan and survey needed to acquire representative data.

Development of a complete, approved survey plan should be

accomplished by the end of FY 80. It is expected that this

effort will rely heavily on the expertise of the Bureau of Census

and the National Center for Health Statistics of HEW.

2.5 Collect Survey Data

By the beginning of FY 81 a position of readiness will have

been achieved to permit field data collection of ergonomics data.

Data collection is currently projected to last for a period of 15

months

.

2 . 6 Load Survey Data

Although the data processing configuration can take any of

several forms, it is anticipated that the data can be loaded into

a central SERDS proces:3or within three months after field data

collection has started, beginning in the second quarter of FY 81

and continuing throughout the survey cycle through the third

quarter of FY 82.

2.7 User Access to Survey Data

Data from the national ergonomics survey will be made

available to system users upon the completion of data collection,

loading, processing and analysis. Thereafter, continuing, online access will be available to users at prescribed times via

data terminals and by means of periodically published data tables

and other forms of output.

2.8 Provide User Translation Support

Data reported in a research paper or obtained from a survey

and the data ultimately used for a given technology application

are not always equivalent. For example, data on the distribution

of the near-point visual acuity of the adult population does not

readily translate into the many possible applications of acuity

data to signal detectability or to the readability of text.

Similarly, measures of human body size are of little use to the

manufacturer of fire-resistant, cold weather or other clothing

until they have been translated into pattern designs, sizing

groupings and the tariif tables which define the number of items

that must be manufactured to match the numbers of persons within

96
the population subset that will use these items. Accordingly, it

is proposed that a continuing service be made available to

provide advice and assistance to industry or government in making

translations from the SERBS data base to particular user

applications. This translation support should be available when

SERDS becomes operational during the last quarter of FY 82.

Although this activity is identified as part of the SERDS

program, it is envisioned that translation support services would

probably not be performed by the SERDS Office itself but rather

by collaboration with a group which currently performs this

function as part of its mission.

2 . 9 Repetition of Survey

No accurate estimate has yet been made of the rate at which

behavioral and anthropometric changes take place in a population.

However, population changes between 1941 and 1977 have been

sufficiently great to render the earlier data obsolete. Looking

ahead ten to 15 years after the 1981 national ergonomics survey

data have been collected, it seems likely that these data will

also become obsolete, thus requiring another survey cycle. An

activity has been included in the plan to cover this contingency

by repeating the survey at some, as yet unspecified, time in the

future, possibly in conjunction with a census survey.

Plan 3 - Plan for Critical Evaluation of Published Ergonomics

Data

Plan Objective : To develop and provide a capability for user

access to critically^-evaluated data from the published ergonomics

literature.

3.1 Define Priorities for Critical Evaluation

Milestone 1.3 (See Table 4) is the establishment of

ergonomics data priorities based on information received from a survey of potential SERDS users. Milestone 3.1 will define

priorities for critical evaluation of the published literature by

comparing the data required to meet these priorities with the

existing published literature to identify those sufficiently

comprehensive sources which justify analysis and critical

evaluation by data analysis centers. This process would be

initiated in the first quarter of FY 78 and would use

bibliographic services to search for and identify candidate

sources of data.

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99
3.2 Evaluate Existing Centers of Expertise

In the past decade a number of universities, colleges,

private consulting organizations and Federal agencies have become

centers of excellence in specialized areas of ergonomics

research. This planned activity will consist of identifying and

evaluating the types and levels of expertise that currently exist

in these centers with the objective of selecting organizations to

become SERDS data analysis centers. Initially, up to six such

centers may be considered in areas such as the following:

• Anthropometry

• Human information processing

• Human sensory processes

• Human performance

• Biomechanics and bioengineering

• Behavioral toxicity

Final decisions regarding these topical areas and their specific

content will be made after the user need survey is completed. In

addition to reviewing candidate centers of specialized expertise,

individual specialists who might be employed to perform critical

reviews on a one-shot basis also will be identified and

evaluated.

It is anticipated that any funds allocated to centers or

individual experts will augment and sustain but not be a substitute for other ongoing sources of financial support. Thus,

the function of critical analysis will augment but not detract

from continuing research programs in the field of ergonomics.

3.3 Select Pilot Data Analysis Center

Prudence dictates that a single data analysis center be

established on a pilot basis for a trial period prior to the

establishment of additional, permanent centers. The function of

a pilot center would be to evaluate, organize and integrate data

in a given area and to generate outputs for the user community on

a continuing basis. These could be offered directly by the pilot

center or be disseminated by the SERDS Office, whichever seems to

offer the most effective service. The effectiveness of the

procedure used by the pilot center and the quality and quantity

of user responses to the service will be monitored carefully for

a trial period. The pilot center will serve as a prototype for

other additional centers.

100
3.4 Develop General Criteria for Critical

Evaluation

This effort is aimed at establishing explicit criteria that

would govern the screening, acceptance and critical evaluation of

information by data analysis centers. It is anticipated that a publishable statement of these criteria will be available in FY

81 at the onset of critical evaluation activities.

3.5 Provide Critical Evaluation Products and

Services

The services envisioned are summarized in Chapters 2 (System

Concept) and 6 (Data Processing and Output)

3.6 Add Additional Data Analysis Centers

After the performance of the pilot center has been evaluated,

other data analysis centers will be added. It is anticipated

that such centers will be phased-in sequentially over a five year

period beginning in FY 82.

Expanded Program

The plan presented above is oriented around the minimum

effort judged necessary to satisfy user requirements for

ergonomics data. Looking beyond this focus, one can envision

that a demand might be created to expand the scope of SERDS to

provide data coverage for other problem areas. Such areas might

include, but not necessarily be limited to: the application of

human science data to problems of skill and knowledge acquisition

and retention; physiological data and their medical applications;

or behavioral and biological data and their application to

forensic medicine and law.

Another form of program expansion might be required in

response to industry requests for ergonomic data for non-U. S.

populations that represent markets for products manufactured for

export by U.S. industry. This demand could be met in part by

unilateral agreements to share data with national ergonomics data

centers in other countries or by a multilateral arrangement under

the auspices of an international counterpart to the Committee on

Scientific and Technical Data (CODATA) of the International

Council of Scientific Unions. Focal points for such an

international arrangement could be the International Ergonomics

Society, the International Union of Psychological Science and the

Abstracting Board of the International Council of Scientific

Unions.

101
Whatever the future demands for expansion, it is

important that the initial focus of SERDS be upon meeting current

U.S. needs. An adequate "track record" of effective services

must be achieved before any expansion can be contemplated and

justified.

Resources Required

Preliminary estimates of required resources for

accomplishing the major objectives of the SERDS program are

summarized in Table 7. Funding sources are not indicated here,

but include NBS, other Federal agency and industry support.

Estimates of the degree of support from each of these sources

cannot be made at this time. (Note: $K is dollars in thousands,

SY stands for staff years.)

Presentation of this preliminary plan cannot conclude

without a comment on the problems and challenges that can be

expected to arise in the development of any scientific data

system. It would be a grievious mistake to assume that this or

any other plan could anticipate and forecast solutions for them

all. Therefore, a large measure of flexibility will be required

in implementing the plan to best meet SERDS' objectives.

In the opinion of the authors, the technologies for

developing an ergonomics data system are within the present

state-of-the art. The major problems to be faced center upon the

intellectual challenge associated with the identification of data

to be included and their extraction, integration and structuring

into a data base of generic and useful information.

When one considers the social benefits that already have

been derived from the proper application of accurate, up-to-date

and representative ergonomics data, the challenge of developing a system to perform that task better than it is now being done

merits acceptance. Perhaps the following forward-looking

comments made by Dr. H. Wallace Sinaiko in the December 1963

issue of Human Factors are closer to becomming realty with this

report:

"not so near to realization, but a technique that will

ultimately serve to keep human factors references up-todate, is the use of automatic, i.e., computer-based

systems. These systems will provide truly dynamic data

bases . . . Users of such data systems will be able to

query them from remote locations . . . Ultimately,

however, this approach may eliminate completely the need

for conventionally written and edited reference

material.

102
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I
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Martin, J.I., Sabeh, R. , Driver, L.L., Lowe, T.D., Hintze,

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McConville, J.F., Churchill, E., Clauser, M.A. and

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O'Brien, R. and Shelton, W.C. Women's measurements for

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33. Roebuck, J.A. , Jr., Kroemer, K.H.E. and Thomson, W.G.

Engineering Anthro

and Sons , Inc. , T§

—aEngineeringJ Anthropometry Methods, New York: John Wiley iii^^^-

34. Ronco, P.G. A bibliography and overview of human factors

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35. Ronco, P.G. Human Factors Engineering Bibliographic

Series , Tufts University, Medford, Massachusetts, May

1966.

36. Rossmassler, S.A. "Critical Evaluation of Data in the

Physical Sciences —A Status Report on the National

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37. Seminara, J.L. In search of ergonomics in the U.S.S.R.,

Human Factors Society Bulletin , 20 , 3-4, 1977.

38. Senaiko, H. Wallace. Some Ideas about the Future of Human

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39. Slonim, M.J. "Sampling," Simon and Schuster, New York,

1960.

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of airline stewardesses. Report #FAA-AM-7 5-2 , U.S.

Department of Transportation, Washington, D.C. 1975.

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Department of Transportation, Washington, D.C, 1965.

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data of infant and child measurements interim data. The

University of Michigan, Ann Arbor (Reprinted January

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43. Snyder, R.G., Spencer, M.L. , Owings, C.L., and Schneider,

L.W. Physical Characteristics of Children, Report

#U .M. -HSRI-Bl-75-5 , Highway Safety Research Institute,

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Data Base : A Preliminary Study Report , NBSIR 74-506,

U.S. Department of Commerce, June 1974.

108
45. Stoudt, H.W., Crowley, T.J., McFarland, R.A. , Ryan, A.,

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Swain, A.D. Development of Human Error Rate Data Bank , Reprint SC-R-70-4286 , Sandia Laboratories, Albuquerque

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49. Webb, E.J., Ccunpbell, D.T., Schwartz, R.D., and Sechrest, L

"Unobtrusive Measures : Nonreactive Research in the

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151. White, R. Personal communication, U.S. Army Natick Lab,

Natick, Massachusetts.

ih

I

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109

APPENDIX A

Minutes of March 16, 19 77, and

March 25, 1977 meetings.

Ill
1

I

I

1
MINUTES OF THE ERGONOMICS DATA COLLECTION MEETING

WITH THE SIZING COMMITTEE, MAIL ORDER ASSOCIATION OF AMERICA*

March 16, 1977

National Bureau of Standards

Washington, D.C. 20234

Attendance : Representing the Mail Order Association of America (MOAA) , Sizing Committee

Fred Birdsong

Michael Feltser

Morton Goldner

Aubrey Jay, Chairman, Sizing Committee

W. M. Lowrey

Jim Niver

Charles Schmitt

Robert Ullman

Representing the National Bureau of Standards

C. W. Devereux

Joel Kramer

Melvin R. Meyerson

J. J. Persensky

Louis G. Porter

Harold P. Van Cott

Stanley I . Warshaw

Opening and Welcome

Dr. J. J. Persensky opened the meeting at 9:02 am.

Participants introduced themselves and their respective

organizations. Dr. Persensky then introduced Dr. Stanley Warshaw,

Director of the NBS Center for Consumer Product Technology and

Dr. Melvin Meyerson, Chief of the Center's Product Systems

Analysis Division. Dr. Warshaw welcomed the Sizing

Committee to the Bureau and briefly described the Center's

mission and origins. He emphasized the importance that the

Center places on the application of human factors data to

soft- and hard-goods design and performance and the importance

of a data base that would provide the human anthropometric

* For further information write or call Dr. Harold Van Cott

or Mr. Joel Kramer (301) 921-3691, Human Factors Section,

Center for Consumer Product Technology, National Bureau of

Standards, Washington, D.C. 20234.

113
and performance data needed in such areas as the sizing and

performance of clothing and other consumer products: appliances,

furniture, and energy -consuming products.

Earlier Efforts on an Anthropometric Survey

Mr. Joel Kramer, Human Factors Section, traced earlier

interest in a National Anthropometric Survey by members of

industry and cited the events leading to a brief feasibility

study of a National Survey done by NBS in 1973. He explained

that as a result of that meeting, industry representatives

requested that NBS conduct a National Survey and that the

Bureau had declined on the grounds that at that time it could

not divert personnel and resources for such a survey but that

the Bureau would be willing to provide technical advice if

some other group, such as a trade association, could undertake

such an effort. Mr. Kramer pointed out that there were

several probable reasons why the Bureau did not act more

positively in response to the industry request. These included

the high cost estimated for the anthropometric survey in the

feasibility study; the lack of qualified Bureau staff

to actually conduct a national survey; and the brief period

and limited funds of the feasibility study which did not

give NBS the time to explore and develop a concept whereby

a data base could be developed without total support in

funds and manpower coming exclusively from the Bureau. He

pointed out the need for careful and detailed planning jointly

by NBS, other Federal agencies, and interested industry groups.

A detailed user needs and priorities survey would provide the

framework and much of the justification for proceeding with

long-term developed of an ergonomics data base.

He estimated that if all went well and the recommendations

of the Pilot Project were accepted by NBS management, further

planning would continue in FY 1978 and collection of

anthropometric data might take place as early as FY 1979.

Van Cott pointed out that the Bureau could not undertake

the survey but might arrange to have it done. He also stressed

the importance of obtaining funding and support from several

other Federal sources, as well as from industry, in further

planning and particularly in actual data collection. He

concluded by commenting that of all of the areas in which data

would be needed, body size data would be given a high priority

and would be a good candidate for the area in which data

collection would start.

The time table now projected by NBS for the development

of a data base was discussed by Dr. Van Cott. He indicated

that a year of further planning would be needed in FY 1978 to

identify cost-effective methods for conducting a national

anthropometric survey, to develop plans and schedules, to

114
obtain NBS approval, and enlist aid from other Federal

agencies and industry. Actual collection of data could not

take place, in Van Cott's opinion, before FY 1979 and might be

later if technical problems were encountered in using offthe-shelf equipment to collect body measurements. In the

event that equipment must be developed, a contractor would

require at least another year to conduct the necessary

engineering development and feasibility tests of measuring

devices. This might delay actual data collection until 1980

or later. Other problems, such as determining the sample

characteristics and size needed to reflect such consumer

variables as age, sex, occupation, might also arise.

Despite these obstacles. Dr. Van Cott pointed out the need

for careful, detailed planning and coordination if any data

were ever to be collected.

Comments by Sizing Committee

Members of the Sizing Committee reiterated their impatience

to get current body size data. They stressed the extent and

scope in terms of the money and labor being expended by the

clothing industry, the importance of proper fit to the

consumer, and the enormous economic cost of garments that

are returned each year due to poor fit . Further urgency is

created by the impending need to convert to metric measurements which cannot be done with existing, obsolete and

inaccurate data based on the 1939-1940 Department of

Agriculture national anthropometric survey. This survey

is no longer useful, forcing industry to rely, at great

expense, on trial and error as the only basis for sizing

clothing and establishing sizing tariffs. Dr. Van Cott

invited industry representatives to document the problems

and costs encountered in not having current sizing data.

Anthropometric Measuring Techniques; State of the Art Review

Dr. Louis Porter, Human Factors Section, reviewed existing

techniques for taking body measurements and compared them in

terms of speed, accuracy, and cost. These techniques range

from classical anthropometry (tapes, calipers, etc.) to

photography including bios tereometr ic devices. In his opinion

it is questionable as to whether bios tereometr ics , despite

rumors to the contrary, could permit the collection of data

on a nationwide basis for a reasonable cost. Dr. Porter

then suggested that the automation of classical anthropometry,

with all of its inherent limits, might still be the best

solution; but that all alternative techniques must be

carefully evaluated before data collection can begin.

115
Industry Comment

Members of the Sizing Committee expressed their concern

that NBS might be striving for more accuracy than necessary

in the collection of body size data. For garment sizes

accuracies of from 1/4 to 1/2 an inch are probably adequate.

NBS representatives pointed out, however, that accuracies

greater than these may be needed for other applications,

such as the design of anthropometric probes for evaluating

product hazards; and that it would be necessary to determine

the maximum accuracy needed if data for diverse applications

were to be collected in any national survey.

Mr. Jay pointed out that raw anthropometric data were

not what apparel manufacturers needed but rather data in the

form of size groupings presented in the manner of existing

NBS clothing size standards. Mr, Jay then made the following

additional points: (1) volumetric data, as well as linear

body measures, are needed in sizing shoes, bras, and other

apparel items; (2) there is a need to consider updating

sizing data by repeating a survey as often as every five

years; and (3) size information must be presented as a function of age, demographic variables and in terms of the

proportions of persons in each category having given

dimensions. He repeated the urgency of the industry's need

and pointed out that the major beneficiary of good sizing

data is the consumer who has a right to proper fitting

garments without trial and error in selection. Mr. Jay

concluded by asking whether a "quick study" could be made

to obtain the needed data, to be followed up by a more

detailed, more precise survey later in time. He then

presented a list of body dimensions (see Attachment 1)

developed by the Sizing Committee which, in its opinion,

covers the data needed not only for clothing but for many

types of hard-goods as well. The list contains 142 dimensions. Of these, 30-40 dimensions as represented in existing

NBS standards, are specially important. These do not,

however, include volume data on such items as foundation

garments, hats, and shoes. Nor do they completely cover

data needed on the aged, disabled, or handicapped.

Further discussion by participants covered the need

for an Advisory Board of industry representatives.

Mr. Lowrey, of Sears, Roebuck, and Company, expressed Sears'

interest in the long-term development of an ergonomics data

base despite the fact that it may not be possible to meet

metric conversion needs. He indicated that it was better

to obtain good ergonomic data later rather than not at all

considering the detailed planning needed for a program that

was assured of success.

The meeting wad adjourned at 3:00 pm by Dr. Persensky.

116
ATTACHMENT 1

SIZING SUB COMMITTEE OF M.O.A.A.

Aubrey Jay, Chairman 11-5-7 3

Subject: Body Measurements to be taken in the Proposed

Biostereometric Statistical Study of the

Population of the U.S.A.

The undermentioned measurements were agreed to by the

above committee in conjunction with representatives of the

Fashion Pattern Industry (Simplicity and Butterick)

It is the thinking of those present at this meeting that

these measurements will supply all of the information required

to construct patterns, grade patterns, and give consumer

sizing information for all types of apparel including intimate

apparel, head and footwear, and gloves.

In addition this information will enable the accurate

construction and sizing of the body forms used in the clothing

industry, as well as shoe lasts.

1. Stature - total height.

2. Shoulder point height.

3. Suprasternale height.

4. Nipple height.

5. Waist height (This should be taken at narrowest part

of adult body [male and female separately] and

related to a vertebra number)

6. Wrist height.

7. Bottom of ami scye height.

8. Neck point height (where shoulder joins the neck

at the highest point)

9. Gluteal furrow height.

10. Middle finger tip height.

11. Hip height (at widest point)

12. Hip bone height.

117
13. Elbow height.

14. Cervical height.

15. Top of knee height.

16. Mid knee height.

17. Bottom of knee height.

18. Crotch height (from apex of body crotch round).

19. Chest depth.

20. Waist depth (measured at #5).

21. Buttock depth.

22. Chest breadth.

23. Back breadth.

24. Waist breadth (measured at #5).

25. Hip breadth.

26. Hip breadth sitting.

27. Under arm length (from bottom of arm scye to wrist

bone protrusion)

.

28. Upper arm circumference flexed.

29. Elbow cir6umference flexed.

30. Half cross back (spine to back scye).

31. Arm length to elbow (spine to elbow with arm bent

and held at right angle to body)

.

32. Arm length to wrist (taken as #31).

33. Waist (measured #5) to chair seat (subject sitting)

34. Posterior neck length.

35. Back waist length (measured at #5)

.

118
36. Total crotch length (measured #5) from back to

front of body.

37. Anterior neck length.

38. Front waist length.

39. Neck base circiiinference

40. Mid neck circumference.

41. Scye circumference.

42. High hip circumference (at hip bone)

43. Hip breadth (at hip bone)

44. Hip depth (at hip bone).

45. Hip/seat circumference.

46. Calf circumference (state where).

47. Calf height (state where)

48. Ankle circumference (apex of ankle bone).

49. Ankle height (bottom of ankle bone).

50. Vertical trunk circumference (at point where neck

joins shoulder)

51. Upper arm circumference (extended)

52. Elbow circumference (extended)

53. Lower arm circumference (extended)

54. Wrist circumference.

55. Shoulder length (from where neck joins shoulder to

end of shoulder bone)

56. Over shoulder circumference.

57. Chest circumference.

58. Waist circumference (measured at #5)

119
59. Upper thigh circumference (as close to where leg

joins body as possible)

.

60. Mid thigh (mid way between upper thigh and top of

knee height)

.

61. Lower thigh.

62. Knee circumference (at bottom of knee height)

.

63. Upper thigh circumference sitting (as per #59)

.

64. Mid thigh circumference sitting.

65. Hand length.

66. Palm length.

67. Hand circumference around thumb.

68. Hand breadth at thumb.

69. Hand thickness (at knuckle).

70. Hand breadth (at knuckle).

71. Finger diameter - 1st finger

72. Finger diameter - 2nd finger

73. Finger diameter - Middle

74. Finger diameter - Index

75. Thumb diameter

76. Finger length - 1st finger

77. Figger length - 2nd finger

78. Finger length - Middle

79. Finger length - Index

80. Thumb length

> (at knuckle)

120
81. Hand circumference around knuckles.

82. Foot length (heel to big toe)

83. Instep length (heel to ball joint)

84. Foot circumference (at ball joint)

85. Foot breadth (at ball joint).

86. Heel width.

87. Foot length (heel to little toe)

88. Foot circumference at instep.

89. Ear to ear breadth.

90. Distance between eyes (point to point nearest

the nose)

91. Distance between eyes (point to point nearest

the temple)

92. Head breadth.

93. Maximum forehead diameter.

94. Cheek to cheek diameter.

95. Top of nose breadth,

96. Nose width at widest part.

97. Upper lip length.

98. Lip length.

99. Cheek bone to cheek bone diameter.

100. Total ear length.

101. Ear length.

102. Head length (front to back).

103. Bitragion - Submandibular arc.

104. Bitragion - Menton arc.

121
105. Bottom of nose to upper lip length.

106. Length from center of eye to bottom of nose.

107. Bitragion - Coronal arc.

108. Sagittal arc.

109. Head circumference.

110. Bitragion - Minimal frontal arc

111. Bitragion - Subnasal arc.

112. Ear protrusion.

113. Bitragion posterior arc.

114. Maximum head diagonal from menton.

115. Head diagonal: nuchae to pronasal.

116. Top of eye to bottom of chin length.

117. Rib cage - Under bust (where breasts joins body)

circumference

.

118. Over chest circumference (at start of breasts).

119. Nipple to Nipple width.

120. Full strap (from nipple to nipple around back of

neck)

.

121. Neck point to nipple length (where neck joins

shoulder a highest point to nipple)

.

122. Neck point to center front waist (neck point see #121)

.

123. Cervical to center front waist length.

124. Scye depth (found by deducting #7 from #2)

.

125. Neck point to front waist (neck point see #121

over nipple and straight down to waist)

.

126. Across shoulder arc width.

122

\ .
127. Across shoulder width.

128. Apex of stomach to apex of seat depth.

129. Armhole depth (front to back)

130. Shoulder slope in degrees.

131. Age.

132. Weight.

133. Plumb line position.

134. Waist to crotch volume.

135. Crotch to knee volume.

136. Knee to ankle volume.

137. Top to bottom of knee volume.

138. Top to bottom of ankle volume.

139. Waist to ankle volume.

140. Left breast volume.

141. Right breast volume.

142. Rib cage volume (see #117) .•

123

I MINUTES OF THE MEETING OF NBS BEHAVIORAL SCIENTISTS ON

THE ERGONOMICS DATA BASE

March 25, 1977

Attendance

John Archea

C. W. Devereux

Jacquie Elder

C. Fried

Dane Harwood

J. J. Kramer

Steve Margulis

M.R. Meyerson

John Molino

CO. Muehlhause

J. J. Persensky

Val Pezoldt

Brian Pierman

Lou Porter

Hal Steinberg

H.P. Van Cott

Product Systems Analysis Division

Auditory Acoustics

Institute for Applied Technology

Human Factors Section

Architectural Research

Human Factors Section

Auditory Acoustics

Architectural Research

Standards Development Services

Sensory Environment

Human Factors Section

Human Factors Section

Office of Housing § Building Technology

Human Factors Section

Performance § Safety Analysis Section

Human Factors Section

Summary

The purpose of this meeting was to describe the concept

for and receive comments on a data base of critically evaluated,

numeric, ergonomics data that could be used by government,

industry, and the academic community in tha planning, design

and evaluation of human-centered systems, products, built

structures, and work and living environments.

Dr. J. J. Persensky, Human Factors Section, Center for

Consumer Product Technology (CCPT) , opened the meeting.

Participants introduced themselves and opening remarks

were given by Dr. Melvin R. Meyerson, Chief of the Product

Systems Analysis Division, CCPT. Dr. Meyerson welcomed

the invited guests and pointed out the importance of human

factors in the Bureau's consumer related activities. He

emphasized the importance of having accurate, up-to-da'te

information on human characteristics that could be applied

to the design of products, systems and environments to make

them safer, less energy intensive and more effective in

performing the tasks for which they were intended.

Dr. Harold P. Van Cott, Chief of the Human Factors

Section, presented a paper that described a concept for a data base of critically evaluated ergonomics information on

125
selected aspects of human anthropometry and performance

that are needed in product design and evaluation. Past

efforts at collecting quantitative ergonomics (human factors)

data were described and found to be deficient in several

respects. The nature and intensity of the need for current,

accurate data in a form that could be readily applied by

industry, Federal and state government and the research

community were illustrated. Although there is a great deal

of data available on human characteristics, the data of

greatest interest and potential applicability consist of

those relatively simple, easily modeled and characterized

structural and performance characteristics (e.g., from human

vision, hearing, and physical anthropometry). Though some

quantitative information is available on other higher order

human processes and performance, such data are of questionable

general izabil ity and their basis for characterization,

modeling or measurement is in doubt.

Dr. Van Cott indicated that a model for an Ergonomics

Data Collection System could take a form like that of the

NBS National Standard Reference Data System (NSRDS) . He

described NSRDS, its mission, orientation and manner of

organization and used it to identify requirements for a system of critically evaluated, numeric, ergonomics data.

He pointed out that although such a data system did not now

exist, the capabilities to form such a system could be

assembled by drawing upon proper representation from

presently available organizations in the Federal, state

and private sectors.

''Dr. Van Cott concluded his remarks by describing the

current lAT-funded pilot project to determine the feasibility

of an ergonomics data system. He pointed out that the first

step in such a system was to assess user needs for specific

classes of data. These needs could then be used to develop

plans, schedules and cost estimates for the future.

Mr. Joel Kramer, Human Factors Section, described the

milestones that are presently envisioned for the FY 77 pilot

project and for continued planning and development of the

data base. He indicated that from the evidence currently

available the module of data for which there appears to be

the greatest need is for anthropometric data. This would

require a national anthropometric survey of the type

considered briefly by the Bureau in 1973-1974.

Following these formal presentations, there was a general

discussion of the concepts that had been described. There

was considerable discussion on the current lack of

standardization of methodology used in data collection and.

126
in some areas of human behavior, of the lack of precisely characterized models. This would require in some instances

rather detailed descriptions for existing data to be usable

and ultimately a major thrust in the area of standards

development for data collection and reporting.

The suggestion was made that existing standards

organizations such as ASTM might be appropriate alternative

vehicles to NSRDS for the development of an ergonomics data

base. However, it was pointed out that although ASTM, ANSI,

and ISO did develop standards they were product specific,

sometimes conflicting with one another, and not usually

generic in their applicability.

The potential applicability of an ergonomics data base

to problem areas other than consumer products, such as

forensic considerations was mentioned by Mr. Steinberg.

Information on blood types and other human properties were

pointed out as instances of need. Mr. Steinberg also

pointed out that court case data might be a source of

information for identifying other needs.

There was a general feeling among the meeting participants

that several areas of NBS activity, for example in hearing

thresholds and work on environmental effects, could both

contribute to the development of a data base and drawn upon

one if it were in existence. Dr. Molino suggested that it

would make sense to start the system with anthropometric

data and then add later, as additional modules, audiometric

data from Edith Corliss' program and other auditory data from

his area of research. The importance of dynamic data

collection was also stressed. o Dr. Muehlhause inquired about the state of critical

evaluation in the behavioral science^ that would be required

to develop a data base. It was pointed out that the efforts

in this area, although limited, were significant.

Dr. Warren Teichner at the University of New Mexico in

Las Cruces, for example, has spent many years in developing

functional relationships by the critical evaluation of data

in the published literature.

Dr. Margulis indicated his endorsement of the concept

and stressed the need to develop standardized and stable

operational measurement methods.

Dr. Van Cott indicated that a cooperative effort by

NBS behavioral scientists would be important in establishing

an ergonomics data system and invited the participants to

consider how and in what ways they might plan to become

involved

127
The general consensus of the meeting was that a collection

of critically evaluated ergonomics data would be worthwhile

and that the concept described appeared to be a reasonable one.

128
APPENDIX B

Supporting Letters

129

riiK OHIO !-i r,\ i i-; I TNiN i :nsi r>

Il.arch 31, 1977

fharlos T.. Mauro . Co-Cr.c ir-u-n

"omirtec. on Civilian ropo.-.etry

A-.orican Society of !lc=h.-nical Ernjinocrr;

Vnitod Engineering Canter

345 47ch rci-eet

^'cv York, York 1-017

Dear Mr. Mauro:

This past wcoh, I lecirned about the plnns for the Bureau of

Standards l!u.Tian Factors Section for a data br.se of snthropo-'icr

ceasurenents . As I understand it, this dsta base -rouid be available

for filling nany needs of business, industry and acade.-nics. I br-.efly ssi7 Dr. John Fechtcr who is with the Hunan Factors Seccio.-. cr.d he invited ne to cona to one of their hasrings or someone else could cone curing this week of March 23 to discuss needs for data. I vas . not able to reach you in tine to see if anyone from our contnittee

could p,o Co the bureau for the nieeting. However, it seens very

important for our conmittee to be a\<'are of the planned study at the

bureau. You n:ay be wall £-v7are of it, but I x/as thinking that we

should be sure that all tha coa-nittee is aware of it and see what

data wculd be uP:>f-:l fcr filling the very needs for which our cotnittee was fornsd

Dr. Fechter tjo'.iIc bs receptive to any infcrnatir.;. ^bout our

corrr.ittee which you r.ipht provide hir. and I would be very intere^t- d

in any furtncr inforr-intic-n concerning their plans.

Francili^ :i. Fir£.bcu:;^h

Associate Dean end Director

cc: Jc'rtn Fcchter

3'.ur:ar. Factors Section

".Ic-tional Dureau of 'Itcndcrds

Roon A353 ?:etr.oro] o^r/ Building

•:ashington, B.C. 2'":^

Floyd L. Laubach

120 Miar.i Drive

Yello"..' r.prin^rs , Ohio 45307

131
Society of Automotive Engineers, Inc.

400 COMMONWEALTH DAIVE. WARRENOALE. PA. 1B096

.. .. _^ - (4.12) 7T6-4.a41

- - Cable Addrass: SOCAUTOENO, PA.

June 28, 1977

or. ti. VanCott

Chief of Hunun Factors Section

i.ational Bureau of Standards

Wasliin-ton , D. C. 20234

Duar Or. VanCott:

During the course of the .N'ational Bureau of Standards conference on June 16,

1977, concerning Voluntary Product Standards, the natter of ^'^BS developinr

information and data in the field of Ergonomics was discussed.

The Society of Automotive Engineers, Inc. (SAE) , as you may know, deals with

standards related to all kinds of vehicles which use an internal combustion

engine. This includes automobiles, buses, trucks, airplanes, aircraft propulsion systems, farm tractors, marine vehicles, motorcycles, snow.;obiles

and others.

'Hie SAE, recognizing the needs to standardize the field of P^rgnnomics (iiuman

Factors Engineering) in 1967, created the Human Factors Engineering Conrrii t tee

.

In 19fa8, the International Standardization Organization Tecnnical Comrnittet 22 on Road Vehicles also saw tl>e need for standards in Ergonomics and created

ISO/TC 22/SC 13, Ergonomics Applicable to Road Vehicles. SAE was requested

to act as the international secretariat of this group.

In addition, SAE ' s Construction ;^nd Industrial Machinery Technical Committee

(CI>'TC) has created a human Factors Engineering subcommittee to work on Ergonomics applicable to off-highway equipment. The ISO Central Secretariat

in Geneva saw the need for a coordinating group and created ISO/TC 159,

Ergonomics. The American National Standards Institute (/VN'SI) asked S,VF to serve as the United States Technical Advisory Group. ISO/TC 159 has ere? ted

five subcommittees. SAE has become the U.S. secretariat for two of these

subcommittees; namely. Subcommittee 3, Anthropometry and Riomechatiics , and

Subcommittee 4, Signals and Controls.

For your information, I am providing to you, with this letter, the sccomplistiments of the S/VE Human Factors Engineering Committee and its current progress

on existing projects. Also enclosed are the two most recent reports of the

ISO/TC 22/SC 13, Ergonomics Applicable to Road Vehicles, as well as the recent

minutes of ISO/TC 159 and Su'icommittees 3 and 4. The SAE does sec the need

"I 132
DEPARTMENT OF HEALTH, EDUCATION,

PUBLIC HEALTH SERVICE

CENTER FOR DISEASE CONTROL

AND WELFARE

NATIONAL INSTITUTE FOR OCCUPATIONAL SAFETY AND HEALTH ROBERT A TAFT LABORATORIES

4676 COLUMBIA PARKWAY. CINCINNATI OHIO 4SZ26

June 1, 1977

Mr. Harold Van Cott

Oiief, Human Factors Section

Building 220, Room 8353

National Bureau of Standards

Washington, D.C. 20234

Dear Mr. Van Cott:

Thank you for meeting with us on May 4 to explain your Human Factors

program and to find out about our research programs.

As you know, NIOSH is concerned with ameliorating or eliminating interactions between a worker's environment and the worker which are harmful

to the worker's health. Two ways in which this interaction is minimized

are by engineering controls and protective equipment. It is essential

to understand and be able to specify quantitatively the characteristics

of the worker which are involved with the harmful interactions as well

as the characteristics which are related to the measures which are being

used to protect the worker. Considered in this general way, the amount

of data on worker characteristics which is necessary to a really satisfactory development of protective equipment test methods and criteria is

potentially very great. Ideally, for a data base of the type NBS is

suggesting, we would like to anticipate for acquisition all possible types

of data which we are likely to find useful in the future as well as the

types which satisfy present needs. Otherwise, repeat studies of similar

populations will become necessary as our research progresses. For efficiency

it would be good to do the survey once and get everything we could possibly

want. However, there does not seem to be a way of specifying everything

we could possibly want. We do not really know what is needed until we get

to the point of having to use it. Also, even if all possible useful data

types could be collected at one time, many worker characteristics have a time dependence which would necessitate periodic resampling of the

population.

One of the strongest points in favor of the suggested NBS data base is

the overlap in data interests of various research organizations. If one survey of the worker population can be utilized by more than one such

organization through appropriate coordination, resources can be conserved.

Also, centralized collection and storage would reduce data search time.

134
Dr. U. VanCott June 28, 1977

for a coordinating group within the United States to have available all of the

Ergonomics work on-going in the various disciplines in the United States.

del

Enclosures

cc: L. P. Ziegler

Sincerely yours,

M. LeRoy Stoner, Manager

Technical Division
Mr. Van Cott

A researcher could be sure that all of the best public data available

had been obtained if he got it from the proposed NBS data base.

The following is a list of worker population data which would be of

current use to our research programs:

1) Facial dimensions

2) General body dimensions

3) Psychological attitudes toward respirator use

4) Worker's physiological response to respirator use

5) Worker tolerance of physical and chemical agents.

It should be pointed out that average values of worker characteristics

are a necessary but insufficient part of the data needed. Distributions

of characteristics are also required. It is important that the data be

categorized as to occupation, industry, sex, locale, age, race and

occasionally other variables.

We look forward to a mutually beneficial participation in the development

of your national ergonomics data base. If you desire information that we have collected, or if you need more details on our data needs, we would be happy to cooperate.

J

Walter M. Haag

- Director, Division of Physical

Sciences and Engineering

135
DEPARTMENT OF HEALTH, EDUCATION.

PUBLIC HEAI_TH SERVICE

CENTER FOR DISEASE CONTROL

AND WELFARE

NATIONAL INSTITUTE FOR OCCU RATION AC SAFETY AND HEALTh

ROBERT A TAFT LABORATORIES

4676 COLUMBIA PARKWAY. CINCINNATI. OHIO 45226

June 27, 1977

Harold P. Van Cott

Chief, Human Factors Section

United States Department of Commerce

National Bureau of Standards

Washington, D.C. 20234

Dear Mr, Van Cott:

I apologize for the long delay in answering your letter of May 11, 1977.

However, I hope that it is not too late for you to take into consideration

our needs in the development of your planned ergonomic data base.

The question which we are most often faced with here at NIOSH is whether

the exposure of workers to certain physical and/or chemical agents is harmful. It is easy to answer this question if an agent occurs at a high enough

level to cause an obvious disease within a relatively short period of time.

However, to assess the effect of a low level of exposure over a long period of

time, e.g. many years or a whole lifetime, it is very difficult to prove

a cause-effect relationship, particularly if the target organ is not known

or differs individually. In such instances, a deterioration of performance

capacity would be a meaningful measure of the harmful effect. At the present,

such assessment could be made only in a longitudinal study. However, if a data base of human performance capacity would be available, such deterioration would be assessable within a relatively short period of time.

The following measures are considered important in assessing human performance

capacity:

Anthropometric measures ;

Mobility of body parts at the joints

Physiological measures ;

Aerobic capacity

Anaerobic capacity

Maximal heart rate

Static muscular strength

Static endurance

Dynamic endurance

Vital capacity

Forced expiratory volume

Maximal breathing capacity

136
Psychological measures ;

Reaction time (simple and complex)

Eye-hand coordination

Vigilance

Learning

Short-term memory

Long-term memory

Problem solving

I would add here that data on performance capacity would not only enable

NIOSH to assess harmful effects of environmental agents but also would assist

industry in fitting the task to the capacities of the worker population,

thus preventing harmful affects due to excessive stress and fatigue. This

is particularly true in materials handling since recent NIOSH studies showed

that low back and other injuries occur more frequently if the load is beyond

a certain percentage of the workers' maximal static strength.

Another area where the ergonomic data base may be helpful is in tool design.

Most important from this point of view are the dimensions, the strength,

and the mobility of the hand and arm.

In the past, we have accumulated data on some of the performance measures

listed above, and we can make them available to you if so desired. We are also ready to provide you with such data to be collected by us in the future.

Please let us know if we can be of any further assistance in working out

details of the ergonomic data base.

Sincerely yours.

Francis N. Dukes-Dobos, M.D.

Chief, Physiology & Ergonomics

137
if SEARS. ROKBUCK AND CO.

CHICAGO. ILLINOIS 60684

SEARS TOWER

National Heaaaua'ters August 24, 1977

Dr. Van Cott

Chief Human Factors Section

National Bureau of Standards

Washington DC, WA 20234

Dear Dr . Van Cott

:

Sears feels that it is necessary to do basic research in the area of

body measurements for the following reasons:

a. Except for a few limited medical studies, most of the anthropometric data in this country is very old.

b. A new study of body measurements is necessary so that new clothing standards can be created as we move to a metric

system of measurement.

c. The current lack of up-to-date standards causes consumer irritation and expense due to poor fitting clothing.

We hope that a new body measurement study will be possible.

Very truly yours

SEARS, ROEBUCK AND CO.

/

W. M. Lowrey '

'

/

Manager, Patterns/Size Fit

Department 817

im/byo

Tu/6507

138
DEPARTMENT OF HEALTH. EDUCATION, AND WELFARE

PUBLIC HEALTH SERVICE

CENTER FOR DISEASE CONTROL

May 25, 1977

NATIONAL INSTITUTE FOR OCCUPATIONAL

SAFETY AND HEALTH ALOSH

94-4 CHESTNUT RIDGE ROAD

MORGANTOWN, WEST VIRGINIA 26505

Mr. Harold Van Cott

Chief, Human Factors Section

Institute of Applied Technology

A-353 Metrology

National Bureau of Standards

Washington, D.C. 20234

Dear Mr. Van Cott:

Dr. John Fechter, of your staff, visited with us on May 13, 1977, to

discuss our potential interests with regard to the development of a human characteristics data base by the National Bureau of Standards.

Our discussions with John were, in my view, very informative and

mutually beneficial.

Our program here in Morgantown is the nucleus of the new Occupational

Safety initiative instituted by NIOSH early in FY-77. The program

will be responsible for developing, initiating, and conducting the

Institute's occupational safety research program including the

testing and certification of personal protective equipment. This

is a multi-disciplinary program which seeks to examine the occupational safety issue from the perspective of the man-machine-environment

envelope. As such, our interest in and need of a broad range of human

characteristics data is keen and essential. Two particular areas of

immediate interest are antropometric measurements and human performance

capabilities

An example of an area of immediate interest is our current program to

develop quantative respirator fit criteria for respiratory protective

devices. This requires the development and use of a "general worker"

facial measurements data base. Should a "standard" data base already

exist, such as in the program you are considering, our problem would

be greatly diminished as would the resources we must now commit to

such a program.

As is no doubt evident from the above, we would strongly support the

establishment of a human characteristics data base by the Bureau. In

addition, I feel that we could meaningfully participate in and

contribute to the data base as it developed.

139
- Mr. Harold Van Cott

The CPSC data base maintained by the Bureau is also of interest to us as many products used in the general population are also used in the

occupational setting. It is my understanding from John that this data

base is also maintained by the Institute of Applied Technology.

I look forward to continued dialogue in this area as your planning

progresses. If we may be of further assistance, please feel free to

call upon us.

Sincerely yours.

/ /John B. Moran " /special Assistant for Safety and

Testing and Certification

Appalachian Laboratory for Occupational

Safety and Health

140
Simpiiciiy Pattern Caina

I 200 MADISON AVENUE, NEW YOR^' :

I ...

August Z, 197 7

Dr. H. Van Cott, Chief Human Factors Section

National Bureau of Standards

Washington, D.C. 20234

Dear Dr. Van Cott:

It has come to our attention that your department is considering

an anthropometric study to provide data on the sizes of people

in this country.

As a leader in the home sewing industry that provides apparel

for a large segment of the population, we wish to urge you

to conduct this study with all haste. It has long been needed

and the need becomes more acute each year.

The apparel industry, as well as commercial pattern companies,

continues to size garments on "educated" estimates... with no

firm statistics. In order to establish standards that will

serve the U.S. consumer with proper fitting clothes, the study

under consideration is of the utmost . importance and will be of

great benefit to the entire population.

The impending conversion to metrics makes the need for such a study most urgent. It would provide the data that would tell

us how to convert.

I urge you to push for the study, and if there is any way m

which this company can help in getting it going, I would appreciate

your letting me know.

Sincerely yours

LHA/es Lilyan H. Affinito

President

OFFICES ATLANTA • DALLAS • LOS ANGELES • NEW YORK * NILES • OMAHA • PITTSBURGH • SAN FRANCISCO

LONDON • SYDNEY • AUCKLAND • JOHANNESBURG • KOLN RH 141
LEONARD J D'AMICO Pr»sKj«nf RAYMOND L MURRAY Btacuti** Vict f>r»sia»nt HY FEINgR. £««cu«v» 0/c*efOf PHILIP J MARGOLIN. TrMSurvr INTERMATION AL ASSOCIATION OF CLOTHING DESIGNERS

7 EAST LANCASTER AVENUE • AROMORE. PA. 19003 • 215/896 7010H

August 4, 1977

Dr. H. Van Cott

Chief Human Factors Section

National Bureau of Standards

Washington, D. C. 20234

Dear Dr. Van Cott:

We understand that there is the possibility for an economic study

concerning the Anthropometric measurements to cover sizing of apparel

for men and boys. This study will also cover various socio-economic

groups in the U.S.A.

At present there are no reliable studies or data concerning the

sizing of men's apparel; therefore, the proposed study has great merit.

In fact, present data is almost meaningless and cannot be converted to metrics.

Tlie proposed study would certainly be of great importance to the

consumer, the retailer, and the manufacturers; as well as apparel designers.

We do require new standards for sizing mens and boys apparel.

Kindly advise.

HF :NZ

cc: Aubrey Jay, J.C. Penney Co.

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CINCINNATI TORONTO NEW ENGLAND , _ NEWARK ITALY 142
April 25, 1977

Mr. H. P. Van Cott

Humaui Factors Section

Center of Consumer Product Technology

Institute for Applied Technology

National Bureau of Standards

Washington, D. C. 2023^

Dear Mr. Van Cott

Relative to the meeting of March l6, 1977 and the need for a new anthropological study.

The attached are areas of concern to our hard lines design

department.

Please keep me informed of any new developments.

Yours truly,

Michael Feltser

Queility Assuramce Manager

Attachment.

cc: S. A. Noreen

R. L. Swanson

QUALITY ASSURANCE 393 FASHION AVENUE/NEW YORK \EW YOHK 1 0OU 143
April 15, 1977

Mr. Michael FelsCer

Quality Assurance Manager

New York Office

RE: National Bureau of Standards Human Factors Study

The Corporate Product Design Department of Montgomery Ward agrees that

there is a need for certain updated and appropriate information which

could be provided to designers and would benefit the consumer in better

looking, quality constructed, easy to use and safe products.

The following are. some of the data we feel would be necessary to make the

study meaningful. Both inch and metric dimensions should be listed.

1. Age and Sex Distributions, as well as Averages and Percentiles in

increments of 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70+

years.

Weight

. Standing Height.

. Erect Sitting Height.

Normal Sitting Height.

Knee Height.

. Popliteal Height.

. Elbow Rest Height.

. Thigh Clearance Height.

Buttock-Knee Length.

Buttock-Popliteal Length.

Elbow to Elbow Breadth.

Shoulder to Shoulder Breadth.

Seat Breadth.

Head

.

. Neck.

. Chest.

. Waist.

Arm and Leg Lengths.

Hand Width and Length.

. Feet.

144
2. Data is needed on people in motion as well as stationary. We need

motion studies and specific product/user interfaces. People by age

and size do things differently - e. g., sitting in a chair, watching

T.V., sleeping, etc.. We need action/reaction times both in normal

use of product situation to dangerous panic times.

3. Being in mass merchandising, both in retail and catalog, data is needed

on the physically and mentally handicapped, child care, senior citizens,

obese individuals, giants and midgets, left-handed versus right-handed

people , etc .

4. V/hat are the occupational categories man falls into? What are his

leisure activities (sports, travel, hobbies, etc.)?

5. How does man react and interpret colors? What colors are most and

least visible? Most contrasts - indoor, outdoor, incandescent,

fluorescent lighting. What about symbols rather than words?

6. What shapes and forms are easier to handle - e. i., shapes of soap,

bottles, handles, knobs, etc.?

7. What are ideal locations and type preference for product controls

by product - e. i., high, low, out-of -sight , pushbuttons, switches,

graphic identification, remote, etc.?

8. We should get man's opinion on standardization of actual sizes for

materials and products. A "2 x 4" piece of lumber is actually

1-5/8" X 3-5/8", a "2 x 2" is actually 1-5/8" x 1-5/8". Pipe sizes

too, should be actual. What about shoe sizes, say 10-1/2 D? How

wide actually is A, B, C, D EEE?

9. What is man's reaction to the new sophisticated electronic con- trols. .. .digital , LED, touch sensitive, etc.?

10. What are man's dislikes? What are his fears of certain products?

T.V. and Microwave radiation? Air Cleaner and Dryer ozone scares?

Flammability . Unsafe construction?

11. Data of health and hygiene could be useful.

Showers versus Baths.

. Eating Habits.

Smoking and Drinking.

Types of Toiletries.

Vitamins.

Eyesight. How many people are 20-20, nearsighted, farsighted?

Hearing. How many people use hearing aids. Sound at a minimum, maximum and overage levels in both open and enclosed

spaces. What about sound imitation? What products are annoyingly loud?

145
12. What products should man change? What new products does man foresee and need?

13. What productshave failed to satisfy him?

14. Incidence of product-related accidents and their causes.

15. We should measure stress and how it affects the human senses and

reactions.

There is some overlap here with the Penney 's and Sears' write-ups and some

of their ideas we haven't mentioned. However, we feel all areas cited

are pertinent and should be considered part of the final format.

As we said at the start of this letter we agree the designers of America

need information, but the time periods and the monetary outputs forecasted

for the multi-phase study seem to us a little extreme. An effort should

be made to gather, add to, edit and distribute the information that

already exists.

The Armed Forces, certain universities, such as UCLA, USC or corporations

like General Motors, and Industrial Design magazine should be contacted.

These resources most likely have much of the human body statistics in a current usable form. An advertisement in the April 18, 1977 issue of

Sports Illustrated magazine shows that Corporation Designers, Engineers,

and Stylists worldwide use hnman factors in achieving their end results.

The product is a BMW automobile manufactured in Germany. Some of the

advertising copy reads as follows:

"Part of the explanation of this phenomenon lies inside the car....

the interior of the BMW 630CS; while richly upholstered in supple

leathers - is ergonomically engineered to the nth degree.

All seats are orthopedical ly molded; all individual seats are infinitely adjustable. Controls are within easy reach and all

instruments are instantly visible in an innovative three-zone

control panel that curves out toward the driver in the manner of an airplane cockpit.

So thorough is the integration of human and machine that the driver

literally functions as one of the car's working parts - the human

part that completes the mechanical circuit."

Once an appropriate questionnaire is established it could be incorporated

with the F-^deral Income Tax Return for distribution and retrieval. When

compiling the data be sure it is presented in human figure diagrams,

bell curves, bar charts and other illustrative means for quick reference.
A suggestion for data gathering on product usages might be to select a group of average families, average singles, etc., and have them record

their reactions and opinions to certain products they own, or are furnished, in their normal everyday life environment. Expose them to

products and activities under their own conditions. Have them record

times used, convenience, most used features, ease of operation, cleanability, etc..

We have one other thought to pass on for input. It has been said that

the American is growing at 0.3 inch a decade. Products have various

lifetimes before they wear out, breakdown or become obsolete. For most

products to last 20 years is more than to be expected and the future

users, if the products are handed down or sold, will grow only 0.6 inch

in this period of time. Maybe we are over emphasizing the change in man as an ever growing body and should consider what is happening in

America. There's the emphasis of compact living quarters, compact

automobiles, compact appliances, food shortages, higher cost of living,

microminiaturization, smaller families, energy, water and time conservation, and thus possibly smaller human beings.

If all this data gathering becomes a reality we will certainly reap the

harvest with product improvements and future developments.

I hope the above thoughts will be supporting input for your presentation

of the need for human factors in the B, C, and D Lines of Montgomery Ward

merchandise

Robert A. Noreen, Manager

Corporate Product Design Department, R fit D 6-5-

cc: Mr. R. L. Swanson, Mdse. Development

147
March 23, 1077

Human Factors Section

Center of Consumer Product Technology

Institute for Applied Technology

National Bureau of Standards

Washington, D.C. 202 3^+

Attention: Mr, Harold P. Van Cott

Dear Sir,

Relative to the need for new anthropological data, the following are some of the reasons why it is imperative to commence such a study as soon as possible;

Current data is almost ^+1^ years old. The relevance of this data

to current body configuration is doubtful, r^articularly when

changes in dietary habits and the infusion of various ethnic types

into the nouulation since the data was taken is considered.

No data is available for adult males, protective headgear, shoes,

hand covering or hosiery.

New accurate data would provide hard and soft goods to be designed

with optimum safety consideration for the consumer.

Sizes or size ranges could be enlarged or lessened providing

greater consumer satisfaction.

The remaining size ranges would accurately reflect proper sizing,

providing for less returns by the consumer, which can relate to

lower prices. This in addition to less frustration or confusion

at the point of purchase.

Metrication - with the impending conversion to this system new data is a requirement . Conversion of the old data cannot be

accomplished in a practical form useable by industry unless we are willing to settle for a standard invented by necessity which

would gerrymander available data.

In synonsis the final beneficiary would be the consumer in the areas of

reducing the plethora of size confusion, and those sizes remaining would

be more accurately built to better service the consumer.

Yours truly,

Miahael Feltser

Quality Assurance Manager

cc

:

L. J."Nolnn

S. owansnn

QUALITY ASSURANCE 393 FASHION AVENUE NEW YORK NEW YORK 10001 148
JCPenney

June 2, 1977

Mr. H. P. Van Cott

Chief, Human Factors Section

National Bureau of Standards

U. S. Department of Commerce

Washington, D. C. 20034

Dear Sir:

Please accept my apologies for the delay in writing to you regarding

our March 16 meeting in Gaithersburg

I cannot express strongly enough the dire need for a new ergonomic

study of the populat ion of the United States. The body size standards

currently issued by your offices are an immccisurable value to the

garment industry; however, their value is undermined by the fact

that the data used, on which to base these various standards, is

30 years old and not totally intergrated and therefore does not

provide a factual or logical procession from childhood through

adolescent into adulthood.

Consumer awareness and consumer demand for correct fitting of clothing,

as well I might add for every other item used by humans, is strongly

felt by all segment of the manufacturing industry. Our responses

to these demands are limited by lack of current factual ergonomic

data on which to base our products.

The Sizing Subcommittee of the Mail Order Association of America of

which I am chairman has for many years stressed the need for a new ergonomic study, and I know that I can speak for them in addition

to myself, in urging your department to immediately take action to

provide us with the standards we need to satisfy the consumers.

While endorsing the need and urging action for this ergonomic study,

I would also urge that the method used in this study should be one where the information captured would be permanently on record and

in such form as to be able to supplement the original information

asked for. I stress this because with this study, I am sure, we will find applications for the use of the data not yet conceived

in our minds. Therefore, it seems to me that stereographics-biostereometrics is the route to go.

J. C. Penney Company. Inc.. 1301 Avenue of the Americas. New York. New York I00i9 149
To: Mr. H. P, Van Cott

Date: June 2, 1977

In closing, I would offer my own personal efforts and conmitment in

any way that you think would be meaningful and helpful to this

proposed study.

I am, yours respectfully,

JCPENNEY COMPANY, INC.

Aubrey Jay

AJ/nc

cc

:

Mr. B. Hahn - M.O.A.A.

150
June 23, 1977

Jantzei^>

Mr. H. P. Van Cott

Chief of Human Section

National Bureau of Standards

U. S. Department of Commerce

Washington D. C. 20034

Dear Mr. Van Cott:

Jantzen recently as a company spent a considerable amount of time

effort and money in attempting to determine what garment sizes

should be used for nominal sizes in Misses and Junior sportswear.

Up until recently we have adhered to the National 3areau of Standards'

body measurements as outlined in PS 42-?0 to determine the critical

measurements of women for various nominal sizes. We initiated a review of what other manufactures were doing and what the retailer

expected from the manufacturer and found that there is a wide

range of garment sizing with identical nominal size labels. I would suggest that to say that there is confusion in sizing in

the market would be an understatement.

In a discussion with fir. Aubrey Jay from J. C. Penney Co. he

mentioned that there was a current proposal for additional

study of body sizes. In my opinion, accurate, up-date information

on body sizes which would result from such a study would be most

valuable in terms of consumer satisfaction and el imination of confusion.

If I can communicate this opinion more to any one who would be of

help in advocating this study, please let me know.

Sincerely,

E, N, Waage

Director of Quality Control

pb

151
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350 Fifth Avenue. New York. N Y 10001

Telephone: (212) 736-8820

September 12, 1977

Harold P. Van Cott

Product System Analysis Division

Building 220, Room A353

Washington. D. C. 20234

Dear Dr. Van Cott:

The Pattern Fa<?hion Indu<;try has brought to our attentio" ynur proposal

for a national study to develop a new anthropometric data base. We

would like to add our support and the support of our Members to your

effort to accomplish this much-needed task.

From reading your paper, "Toward the Collection of Critically Evaluated

Ergonomics Data", we know you are aware of the historical sizing difficulties of the apparel industry in general. Our move toward metrication

offers a unique opportunity for the industry to reevaluate and standardize sizing -- and consequently reduce SKU's, inventory investment and

inefficient stocking. But that standardization can only be effective if we have current and accurate body sizing data with which to work.

We in the home sewing industry have an additional reason for wanting

anthropometric data developed. A recent study conducted for our Association shows that one of the greatest potential barriers to a successful

sewing experience by a consumer is fitting the garment. We could be so much more effective in helping the consumer overcome that problem if we

had accurate data on which to base product instructions and educational

materials and services.

Please keep us posted on the progress of your project, and call on us if we can be of further service. We will checK periodical ly with you and/or

Joel Kramer to see what other support we can give, either documentation

or communication urging federal funding.

S)ncerj?Ty,

Leonard Enni'S

Executive Vice President

LE:pk

cc: Joel Kramer

Alma Cunningham
Mr. C. W. Devereux

Standards Development Service Section

National Bureau of Standards

Washington, D. C. 20234

Dear Mr. Devereux:

The American Apparel Manufacturers Association is in full support

of the proposal of the National Bureau, of Standards, to develop a new

anthropometric data base for standard- bod-Y measurement in this country.

The AAMA Board of Directors-,, at- i-ta Sep^tember 26 , 1.977 meeting,

voted the following resolution:

"That in order for the apparel industry to design properfitting garments , and in order for the National Bureau of

Standards to issue proper specifi.cati.ons , body measurements

of our American population are needed.

"That because of the complexities of developing an anthropometric

data base on which to develop appropria.te. standards for apparel,

the project should be undertaken by the National Bureau of

Standards

"Development of a National Anthropometric Data Base by the

National Bureau of Standards, has the support of the major

retailers

"Be it therefore resolved that the American Apparel Manufacturers

Association endorses the need for de.velopment of this data base

and urges prompt action to achieve the necessary finding so the

National Bureau of Standards- can proceed with the project as proposed .

We will be. anxious to receive news of the implementation of this

program, and pledge the full support of this Association.

Cordially yours,

Ellis E. Meredith

President & Chief

Operating Officer

EEIA : j sh

cc : Robert Ullman

11 NO. KENT S T R e ex • A »»L I N • T O N , VIRGINIA 2-2 209 * PHONE (703) 524.-1864-

153
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350 Fifth Avenue. Nevy Vork. N Y lOOOl

Telephone: (212) 736-8820

November 14, 1977

Harold P. Van Cott

Product System Analysis Div.

Building Z20, Room A353

Washington, D.C. 20234

Dear Dr. Van Cott:

Mr. Ennis has asked me to reply to your letter of September 20. As

mentioned in his first letter, our Association research shows that

while many women sew for reasons associated with a better fitting

garment, we also find that this is one of the most difficult aspects

of the sewing experience for a consumer to complete successfully.

Good anthropometric data would, first and foremost for all clothing,

provide the basis for more accurate standard garment sizes representative of the population at large. Of this you are already aware.

Secondly, specifically in relation to sewing, a consumer here has the

option of making adjustment for deviations from standard body measurements. Sewing thus provides many with a better alternative than readyto-wear for appropriately-fit clothing in fact for thousands of consumers perhaps the only way to achieve that end.

For us to be successful in fulfilling the need for such an alternative,

not only norm data, but also frequent deviations-from-the-norm statistics would be helpful. If, for example, a standard female figure is

36-26-36, and we could predict that an additional 20% were 36-26-38, we could provide instructions for large hip adjustment on all patterns,

thus satisfying the needs of a substantially larger number of consumers

with the same standard product. Additionally, frequent deviations from

the norm could provide the basis for much more simplified fitting textbooks and educational materials. At present, many such materials discuss

every possible alternative. How much simpler and less foreboding they

would be if they could treat the "20 most frequently needed fitting

adjustments"

.

I hope the above is of some help in your program,

further service, please call.

-./

If we can be of

Betty Ann Watts

Communications Director

BAW:pk

154
HIUP STEUEnS

SeSSlSTES LTD

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November 21 , 1977

Dr. Harold P. Van Cott

Chief

Human Factors Section

United States Department of Commerce

National Bureau of Standards

Washington, D. C. 20234

Dear Dr. Van Cott:

It has been called to my attention in the October issue of APPLIANCE ENGINEER

that you are interested in soliciting the comments of people who would be interested

in having a Human Factors Data System within the National Bureau of Standards.

As a member of the Industrial Designers Society of America as well as chairman

of the Government Affairs Committee and a past chairman of the Product Safety

Committee, I think the idea is very commendable. There is a need for sippUance

designers as well as many product designers to call or write a Federal Clearinghouse which would be able to provide design human factors data within a very short

amount of time. Normally it is impossible for us to spend a great deal of research

tim>e to find the critical human factors data because our budgets are limited and

product development schedules are critical. We normally have to rely on material

in our office.

Help from the Bureau of Standards in this particular area would be greatly appreciated. I am sure from my own experience as a consultant industrial designer I would support you in such an effort.

155

APPENDIX C

Remarks made by Dr, Julien M. Chris tensen

and Dr. Richard W. Pew at a meeting of

government agencies convened at NBS on

March 29, 1977, to discuss the concept of a National Ergonomics Data Base.

Drs. Christensen and Pew were retained as

consultants to NBS Pilot Project Staff.

157
!

I

fi

Si

I,
Reflections on the Development of an

Ergonomics Data Base

Introduction

Just as innumerable tangible benefits have been

realized from the establishment of data bases in the

physical sciences, so will impressive benefits be derived

from corresponding efforts in Ergonomics, In these remarks,

I will examine the nature of the need for a data base in

Ergonomics and some of the benefits that will be derived

from this program. A few of the special problems attendant

thereto will also be mentioned.

Before beginning this examination, however, we feel

that a word of approbation to the National Bureau of

Standards is in order for its explicit acknowledgement of

the need in our technological society for an Ergonomics data

base and for expression of its willingness to explore such a program with its resources and with its considerable

prestige which is based on its past demonstrations of

scientific thoroughness and excellence.

The Need

Statistics on accidents, mental health problems,

environmental effects and societal effects dramatically

support the contention that incompatibilities of significant

dimension exist in our highly technical civilization. That

incompatibilities exist should surprise no one since

societies are a reflection of interactions among people and

between people and things whose degree of complexity only

recently has been appreciated and, even when appreciated,

are acknowledged as being far from adequately understood.

The science of Ergonomics, or human factors, is

evidence that a few people have recognized that our

understanding of these interactions is rendered uncommonly

difficult because of the lack of information from the

biological and behavioral sciences that can be used

appositively with information from the physical sciences in

the development of the artifactual systems that characterize

modern society. Most engineers, including those in the

universities who are training their successors, have been

painfully slow to acknowledge that since they, perhaps more

than the members of any other profession, are responsible

for the structure of technical societies, it follows

inevitably that, to no small degree, they then are

159
determiners of human behavior. We have often suggested

that, while psychologists, sociologists and others study

human behavior, in technical societies it is the engineers

who, through their design of empirical systems, to a very

significant extent, determine behavior. If one needs to be

convinced of this, we suggest that he simply try to live

even a single day without touching, seeing, or in any way

interacting with products designed by man.

It is not paradoxical that one group of engineers,

namely, those engaged in the development of military

systems, accepted somewhat earlier than other groups of

design engineers their responsibility to take into account

man's capabilities and limitations when designing and

developing the systems for which they had accepted

responsibility. This was so because generally the designers

of military systems have to extract the last bit of

performance from each of the system components, whether

those components be organic or inorganic, and, insofar as

possible, to make provision for the manifestation of that

performance under the most adverse of circumstances. Such a

design milieu demands that every bit of available

information on every component, human or material, be

considered because the designer can be sure that potential

adversaries are doing the same.

It is fair to conclude from all of this, at least as

far as the United States of America is concerned, that there

would be no science of Ergonomics as it is now known had

military support for it not existed during the past 30

years. The fact that insufficient data existed, or exists

even today, has only served to sensitize them to the need

for their continued support and to increase their

determination and that of other agencies such as NASA, to

support the exploration for that which is lacking. NASA

like the Department of Defense, is called upon frequently to

place man, and to expect him to perform, in environments

different in the extreme from that for which natural

selection prepared him. This derivation will be carried

only one step further by pointing out that the Department of

Transportation has significant programs in Ergonomics,

brought about, no doubt, by the realization that the

operation of commercial and private vehicles of all types

places demands on man that accident statistics strongly

suggest have exceeded his capabilities.

Unfortunately, the lessons that should have been

learned from experiences in these dramatic and even exotic

160
circiamstances have been transferred in significant measure

to only a few of the remaining sectors of our society.

ThuS/ the USA still suffers over 14,000 fatalities per year

in its industries and, even more appalling, approximately

twice that number, or 28,000 fatalities per year, in its

homes. Nonfatal injuries are numbered in the millions;

economic costs are counted in the billions of dollars.

What is the solution? As with any problem, the first

step in the solution is to recognize that a problem exists.

The second is for the members of our society to demand

safer, better designed products. The third is for

management to respond and demand that its engineering staffs

assume responsibility for safe, effective design that is at

least equal to the safe use or safe practices philosophy

that, as the well-known product liability attorney, Harry

Philo, observes, has dominated American thinking throughout

our history. In fact, product liability suits are

forcefully bringing to the attention of the designers and

developers of empirical systems their special responsibility

to those who must operate, maintain, live with or in, or

otherwise interact with their products. In a sense, th^

courts are establishing Ergonomic standards.

The ultimate solution to the problems just described

presumes the existence of principles and data of quantity

and quality that do not currently exist. The establishment

of the NBS Ergonomics Data Base will do much to consolidate

what is currently known and, equally important, demonstrate

what is not known.

This observation leads us, quite naturally, to an

examination of some of the special problems associated with

gathering the data needed for the Ergonomics Data Bank.

Special Problems

The data of the social sciences and the gathering of

such data presents problems that are not found, at least to

the same degree, in the physical sciences. One of the chief

problems is varability—variability not only between people

and within people at a point in time but variability over

time. Provision must be made for keeping the NBS Ergonomics

Data Base current since, unlike certain basic data in the

physical sciences, basic data in Ergonomics varies over

time.

161
Adequate sampling is another critical problem in

Ergonomics. Much of the current USA data is based on

experiments conducted on military or other special

populations. Only limited information is available

regarding the generality of these data with respect to the

entire U.S. population and even less is known with regard to

their generality to foreign populations.

Much of the current data is difficult for engineers to

use directly in the solution of design problems. For

example, functional relationships often are lacking. Data

are often expressed in scalar values that are not of the

ratio type (thus making trade-offs difficult) and often not

scaled at all. Constants, as known in the physical

sciences, are scarce. Criteria are frequently inadequate,

particularly with respect to sensitivity to Ergonomic

variables. It is hoped that the Ergonomics Data Base will

focus attention on the needs that exist for additional

research in areas such as these.

The theoretical understructure for Ergonomics is

generally that of traditional experimental psychology,

experimental physiology and others of the organic sciences.

These theories, though often excellent in concept and

formulation, do not usually reflect the possible impact of

high technology on the definition of their variables or the

interaction of their variables with changing technological

conditions.

Ergonomics researchers have yet adequately to address

questions of enormous importance such as sexual differences,

motivational effects, cognitive functions, and many others.

While the material in this section may discourage some,

it was not so intended. Rather it is hoped that it will be

accepted as one of the great challenges of the scientific

age. As Alexander Pope said, "The proper study of mankind

is man." The time is now ripe for scientists and engineers

to join forces, bringing to bear on these problems the

common and unique combination of their

scientific/engineering training and heritage. It could

result in the development of what Bray many years ago called

the need for a useful "technology of behavior."

Let us now examine some of the many benefits that will

be derived from this technology with its attendant data

base

.

162
The Benefits

As has already been suggested, making available to

designers in general what is already known in Ergonomics

would be useful to the designers of many additional

commercial and industrial products. This is so because the

lag that exists between discovery and application exists in

Ergonomics as surely as it exists in other scientifics

areas. Present knowledge, if applied, would make possible

the design of much safer, more effective commercial

products, industrial tools, etc. even if another human

factors experiment were never to be conducted. One reason

that product liability suits are frequently so successful is

that the designers did not even use the data that had been

available for years at the time they formulated their

specifications

Before we place the entire blame for this state of

affairs on the designers, however, we should consider the

fact that those who educated them probably never insisted

that they include any training in Ergonomics in their

courses of study.

The Ergonomics Data Base will make established data

more readily available to all potential users. Equally

important, the consolidation and presentation of what is

known will make glaringly evident that which is not known.

The NBS Ergonomics Data Base should provide a rich source of

experimental hypotheses for investigators in Ergonomics.

It is hoped also that a further recognition by

engineering management of its responsibilities to society

will cause them to demand educational experience in

Ergonomics for their engineers. This should finally

convince engineering educators that they must broaden their

curricula to include training in Ergonomics. It is

difficult to understand why the educators have not been the

leaders instead of the followers in this regard.

The previously mentioned recognition of deficiencies in

the Ergonomics data bank hopefully will foster a new and

potentially, very fruitful relationship between

investigators from the biological and behavioral sciences on

the one hand and physical and engineering science

investigators on the other hand. This interaction will add

to the development of a more adequate data base, with

improvement in systems and products —improvements especially

in terms of such criteria as safety, economy and social

163
suitability, perhaps reducing the terrible annual toll of

over 100,000 lives and over 30 billion dollars of our

resources in the U.S. from all accidents.

Another benefit may be (although this is by no means

certain since there is evidence that is has not happened in

the physical sciences) the reduction of the time lag between

scientific discovery and engineering application. J.C.R.

Licklider of MIT has commented frequently on the need to

find ways to make scientific discovery flow quickly,

naturally, and easily into technological application.

Hopefully, the Ergonomics Data Base may help achieve this

goal.

The previously mentioned interaction between Ergonomic

scientists and engineers will result in better definition of

experimental variables as well as criteria which will

increase the utility of both underlying theory and specific

experimental results. Functional relationships, with

abscissae capable of engineering manipulation and, thus,

useful in the ever-present trade-off situations of

engineering design, will replace expressions of simple point

differences. Investigators in the writer's primary field,

experimental psychology, will find that optimal definition

of variables from the point of view of theoretical

development may not be coincident with that required for

purposes of engineering design. In fact, the development

over the past 20 years of the field of inquiry that has come

to be known as "applied experimental psychology" is tacit

recognition of this fact.

Finally, as mentioned previously, this enlarged

awareness of the responsibilities of engineers and their

supporting scientists in this technological era will add new

dimensions to the measurement of systems effectiveness.

Concepts such as product safety, job enrichment, and social

utility will assiome increased importance. Hopefully, the

result will provide convincing rebuttal to those who see as

the only solution a rejection of all technology and a return

to a primitive existence. We need not less technology; we

need better technology. The establishment of the Ergonomics

Data Base represents a significant step toward the

achievement of that worthwhile goal. It merits the full

support of all who are interested in the development of a society that, for better or for worse, is irrevocably

committed to the technological approach for solution of its

problems and the enrichment of the lives of its members.

Julian M. Christensen, Ph.D

Professor and Chairman

Department of Industrial Engineering

and Operations Research

Wayne State University

Detroit, Michigan

164
Comments on the Development of a Critically-Evaluated

Ergonomics Data Base

Introduction

The concept of a centralized repository for carefully

screened ergonomics data is an appealing one and it makes

emminent sense for NBS to be the focus of this kind of

activity, both because of the role such a data collection

could play in NBS ' product safety and performance activities

and because of the historical role of NBS as the national

point of contact for scientific and technical standards.

Given the state of the art in ergonomics, however,

development of a repository of useful data will require

careful planning and preparation, so that it does not become

just another exercise in data collection that looks good on

paper but is really applicable to few individual uses. In

order to set this effort apart from a simple collection of

technical reports and journal articles, it will be necessary

to address three issues: 1) identification of data needs

and availability; 2) collection and representation of the

data in a form that is useful for designers and

practitioners, rather than (or perhaps as well as)

scientific investigators; and 3) imposition of quality

control screening on the data that are to be admitted to the

data base. Let us examine each of these issues in turn.

Identification of Data Needs and Availability

An important step in the planning phase of this

undertaking is the identification of the target population

of users for whom the data are to be responsive and, within

each such population, to identify the kinds of data that

would be useful. One purpose of this meeting was to

sensitize various government agencies to this project so

that they could begin to express their own needs. Further

such meetings are being undertaken to identify potential

users among particular product groups, such as clothing

designers or appliance manufacturers. Here it also should

be possible to contact trade associations and manufacturers

associations to get in touch with the right populations of

users.

With respect to product safety and performance, the

NEISS data base may be a useful source of needs through

retrospective analyses and it might also be helpful to

examine a Scimple of product liability law cases in which the

pivotal issue was one involving ergonomic considerations.

165
While no single legal case can establish a national need, we

should be looking for collections of cases which have needs

in common.

A second consideration in defining classes of data for

inclusion should be the maturity of the methods used to

collect the data. Data are only as good as the methods used

to collect them, and for some purposes the statement of

scientifically sound and acceptable methods are as important

as the data themselves. While it seems likely that data on

the workload demands of certain classes of tasks may be

desirable, methodology in this field has not progressed to

the point where one could place high confidence in data

purporting to estimate such workload demand. On the other

hand, methods of physical anthropometric measurement are

well established and a great contribution could be made by

systematizing and augmenting the data in this field in ways

that are oriented toward direct application. Similarly,

basic visual and auditory functions are well defined and

should be relatively easy to incorporate into a data base in

useable form.

The main point here is that converging operations

focused on data needs on the one hand and reliable data

availability on the other should be undertaken to define the

candidate classes of data to be included. These efforts

should be undertaken with modest goals at first, to meet a

few well-defined needs, and then gradually expanded as

experience accumulates over time.

Preparing Data in a Useable Form

A fact of life in the development of scientific data

concerning human performance capacities and limitations is

that most often the individuals collecting the data are

concerned with basic science issues and do not have in mind

potential applications at the time the data are collected.

As a result the relevant data are fragmented and buried in

journals and reports not readily accessible to the applied

commiinity. Often they are expressed in ways useful for

testing hypotheses but not for describing functional

relations between variables under the designers control and

the resultant performance effects.

In some cases, comprehensive literature reviews exist

which can form the basis for the reorganization and

summarization of design oriented data. In other cases it

will be necessary to commission specific parametric studies

166
which sample a suitable population and explore the range of

parameters of interest to the user population. Since so

little of the performance literature has dealt seriously

with individual differences, it will frequently be necessary

to collect enough data so that it can be expressed in terms

of percentile distributions as a function of the relevant

parameters. It is my feeling that one of the most

significant contributions that NBS could make would be the

commissioning of studies of this kind which take what is

known and prepare a parametric data set that expresses it in

quantitative terms that would permit real design decisions

to be based on it. This is an aspect of our science that

has been almost totally neglected.

In the course of analyzing needs for data, it may also

be possible to identify new ways in which the data need to

be organized in order to make them applicable to the problem

identified. A case in point is the development of the Eye

Ellipse by the Society of Automotive Engineers. Automotive

interior designers are not as interested in the physical

location of the eye when an observer is seated in an

automat ive seat as they are in what the observer can see

from that position. The Eye Ellipse expresses in percentile

terms the three-dimensional locus of lines of sight

available to an observer. NBS' role in cases like this

might not be one of directly funding such developments but

rather stimulating the relevant industry association to

undertake the project for later inclusion in the data base.

Quality Control

Regardless of the subject matter that ultimately is to

be included in the data base, paramount concern should be

given to ensuring that the data are reliable, repeatable and

representative of the most advanced methods of data

collection and analysis available in the field. To achieve

this purpose, I would recommend the establishment of a panel

of outside specialists ; perhaps they could be formalized as a

review board, representative of the ergonomics fields to be

considered for inclusion. This board should have the

opportunity to review plans for new data collection and be

the final decision body to determine what data are to be

made available to the commiinity at large.

Summary

The idea of a critically-evaluated ergonomics data base

is an important one. It has the potential to be useful so

167
long as the project includes a component oriented to

identifying real data needs, a component concerned with

expressing the data in terms meaningful to the population of

potential users of the data and, finally a component that

will ensure that only data of highest quality and

reflecting the state of the art in the field will be made

available to the user communities.

Richard W. Pew

Bolt Beranek & Newman

Cambridge, Massachusetts

168
MBS-l UA (REV. 7-73)

U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR RF.PORT NO.

NBSIR 77-1403

2. Gov't Accession

No.

4. TITLE AND SUBTITLE

A STANDARD ERGONOMICS REFERENCE DATA SYSTEM:

THE CONCEPT AND ITS ASSESSMENT

3. Recipient's Accession No.

5. Publication Date June 1978

6. Performing Organization Code

7. AUTHOR(S) H.P. Van Cott, J.J. Kramer, V.J. Pezoldt,

L.G. Porter, C. Fried. J.V. Fechter. J.J. Persensky

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS ^j^jj W.H. Teichner

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, D.C. 20234

10. Project/Task/Woric Unit No.

11. Contract /Grant No.

12. Sponsoring Organization Name and Complete Address (Street, City, State, ZIP)

National Bureau of Standards

Institute for Applied Technology

Washington, D.C. 20234

13. Type of Report & Period Covered

Final

14. Sponsoring Agency Code

15. SUPPLEMENTARY NOTES

16. ABSTRACT (A 200-word or less factual auamary oi moat sigfiilicant information. If document includes a significant

bibliography or literature aurvey, mention it here.)

This report culminates a feasibility study effort aimed at

assessing the needs of industry, government and the research

community for standard ergonomics (human factors) data, proposing a

system concept and preliminary plan for the development and operation

of a standard ergonomics reference data system (SERDS) and assessing

the scientific and technical challenges to be met in system

implementation. The data base proposed here would provide, for the

first time, a single point of access to reliable, current

anthropometric, behavioral and physiological data for application

to technology design. Critically evaluated numeric data,

standardization and the conduct of a National Ergonomics Survey

are the major focal points of the system concept.

17. KEY WORDS ("six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name; separated by semicolons)

Anthropometry; consumer product technology;

engineering psychology; ergonomics; human engineering; human factors;

human performance; product safety; standard reference data

18. AVAILABILITY [XXUnlimited 19. SECURITY CLASS

(THIS REPORT)

21. NO. OF PAGES

r

"* For Official Distribution. Do Not Release to NTIS

UNCL ASSIFIED

164

1

' Order From Sup. of Doc, U.S. Government Printing

Washmeton. D.C. 20402. SD Cat. No. CI 3 Office 20. SECURITY CLASS(THIS PAGE)

22. Price TM—

j

1 XI Order From National Technical Information Service

Springfield, Virginia 22151 (NTIS)

UNCLASSIFIED

$8.00

USCOMM.DC 29042



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