May 2014

NASA/TM2014-218263

NESC-RP-12-00774

 

Computer-Aided Design (CAD) Tools to 

Support the Human Factors Design Teams

Cynthia H. Null/NESC

Langley Research Center, Hampton, Virginia

Mariea Dunn Jackson, Trey Perry, Jason C. Quick, and Jack W. Stokes

Marshall Space Flight Center, Huntsville, Alabama
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May 2014

NASA/TM2014-218263

NESC-RP-12-00774

 

Computer-Aided Design (CAD) Tools to 

Support the Human Factors Design Teams

Cynthia H. Null/NESC

Langley Research Center, Hampton, Virginia

Mariea Dunn Jackson, Trey Perry, Jason C. Quick, and Jack W. Stokes

Marshall Space Flight Center, Huntsville, Alabama
Available from:

NASA Center for AeroSpace Information

7115 Standard Drive

Hanover, MD 21076-1320

443-757-5802

Acknowledgments

The team acknowledges the assistance of Mr. Steven Gentz, NESC Chief 

Engineer at MSFC, for valuable guidance in completing this work. The team also 

acknowledges those who volunteered their time to serve as participants in the 

motion capture sessions.

The use of trademarks or names of manufacturers in the report is for accurate reporting and does not 

constitute an official endorsement, either expressed or implied, of such products or manufacturers by the 

National Aeronautics and Space Administration.
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Computer-Aided Design (CAD) Tools to Support the Human 

Factors Design Teams 

Marshall Space Flight Center Virtual Environments Laboratory 

April 10, 2014
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Report Approval and Revision History 

NOTE: This document was approved at the April 10, 2014, NRB. This document was 

submitted to the Acting NESC Director on April 21, 2014, for configuration control. 

Approved:

Acting NESC Director Date 

Version Description of Revision Office of Primary 

Responsibility Effective Date 

1.0 Initial Release Dr. Cynthia Null, 

NASA Technical 

Fellow for Human 

Factors, ARC 

4/10/2014 

Original Signature on File (MK) 4/23/14
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Table of Contents 

Technical Assessment Report 

1.0 Notification and Authorization ..................................................................................................... 6

2.0 Signature Page ................................................................................................................................ 7

3.0 Team List ........................................................................................................................................ 8

3.1 Acknowledgements ................................................................................................................ 9

4.0 Executive Summary ..................................................................................................................... 10

4.1 Background .......................................................................................................................... 10

4.2 Approach .............................................................................................................................. 10

4.3 Results .................................................................................................................................. 11

4.4 Forward Work ...................................................................................................................... 12

5.0 Assessment Plan ........................................................................................................................... 13

6.0 Problem Definition, System Requirements, and Implementation ........................................... 14

6.1 Problem Definition ............................................................................................................... 14

6.2 Scope and System Features .................................................................................................. 15

6.3 Ground Rules and Assumptions ........................................................................................... 16

6.4 Operational Definitions ........................................................................................................ 17

6.5 Technical Implementation .................................................................................................... 18

6.6 Motion Capture Sessions...................................................................................................... 21

6.7 Risk Assessment .................................................................................................................. 32

7.0 Data Analysis ................................................................................................................................ 35

7.1 Overview ............................................................................................................................. 35

7.2 Database Review .................................................................................................................. 35

7.3 Site Hosting and IT Security ................................................................................................ 36

7.4 GSDO Program Initial Baseline Work ................................................................................. 37

7.5 Mockup Development .......................................................................................................... 39

7.6 Motion Data and CAD Transferability ................................................................................ 39

7.7 Motion Data - Processing and Playback .............................................................................. 40

7.8 Motion Data - Calibration and Capture ................................................................................ 41

7.9 Motion Data - Post-Processing ............................................................................................. 43

7.10 Motion Data - Observations, Issues, and Improvements ..................................................... 46

7.11 Motion Data - Fingers and Hands ........................................................................................ 48

7.12 Motion Data - Aligning Positions ........................................................................................ 50

7.13 Task Performance................................................................................................................. 50

7.14 Human Factors Analysis ...................................................................................................... 52

7.15 NIOSH Lifting Limits .......................................................................................................... 54

7.16 Database Implementation ..................................................................................................... 54

7.17 Website Interface ................................................................................................................. 55

8.0 Findings, Observations, and NESC Recommendations............................................................ 56

8.1 Findings ................................................................................................................................ 56

8.2 Observations ......................................................................................................................... 57

8.3 NESC Recommendations ..................................................................................................... 58
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9.0 Alternate Viewpoint ..................................................................................................................... 58

10.0 Deliverables .................................................................................................................................. 58

11.0 Lessons Learned ........................................................................................................................... 58

12.0 Recommendations for NASA Standards and Specifications .................................................... 59

13.0 Definition of Terms ...................................................................................................................... 59

14.0 Acronyms List .............................................................................................................................. 60

15.0 References ..................................................................................................................................... 61

16.0 Appendices .................................................................................................................................... 62

Appendix A. Operational Definitions ..................................................................................................... 63

Appendix B. Mockup Configurations and Subtask Examples ............................................................... 65

Appendix C. Research Session Tools and Forms ................................................................................... 68

Appendix D. Motion Capture – User Guide and Lab Processes ............................................................ 80

Appendix E. Data Organization and Naming ........................................................................................ 84

Appendix F. NASA Program Risk Scorecard and Ratings Table.......................................................... 87

Appendix G. Database Design Structure and Software .......................................................................... 89

Appendix H. Database Website Interface – July 31, 2013 version ........................................................ 97

Appendix I. Human Research Protocol and Consent Form ................................................................ 102

Appendix J. National Institute for Occupational Safety and Health (NIOSH) Lifting Equation 

Occupational Safety and Health Administration (OSHA) .............................................. 112

Appendix K. Phase 2 Quick Look Test Reports ................................................................................... 116

List of Figures 

Figure 6.4-1. Operational Levels Defined for Motion Capture Planning and Database Content ........... 17

Figure 6.5-1. Initial Mockup of Database Search Page .......................................................................... 20

Figure 6.5-2. Initial Mockups of Database Results Pages ...................................................................... 21

Figure 6.5-3. Concepts for Website Flow and Objectives ...................................................................... 21

Figure 6.6-1. Study Participant in Motion Capture Suit and Cap with Reflective Markers; 

Researcher taking Anthropometric Measurements ........................................................... 22

Figure 6.6-2. Mockup and Video Configurations during Motion Capture Study at MSFC 

VEL ................................................................................................................................... 23

Figure 6.6-3. Camera Mounting Structure and Workspace at MSFC VEL ............................................ 24

Figure 6.6-4. Vehicle Hatches, GSE Shelf and Platform, Battery LRU Mockups used during 

Phase 1 .............................................................................................................................. 24

Figure 6.6-5. Sample Mockup Configurations with Participants Performing Subtasks during 

Phase 1 .............................................................................................................................. 25

Figure 6.6-6. Progression from Solid-surface Plywood to Wireframe Steel Rod Hatch Mockups ........ 26

Figure 6.6-7. Phase 2 Worksite Mockup Constructed with Steel Rod and Multi-insertion Connector 

System ............................................................................................................................... 26

Figure 6.6-8. Progression from Human Participant with Reflective Markers, to Motion Analysis 

Joint Location Data, to Steps for Cortex Software Skeleton, to Jack Software Avatar 

Model ................................................................................................................................ 27

Figure 6.6-9. VEL Work Breakdown Approach .................................................................................... 29

Figure 6.6-10. File Naming Conventions and Folder Structure of Downloadable .zip Data Packets ...... 31
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Figure 7.7-1. Example of Creating a Motion Sequence by Combining Channelsets ............................. 41

Figure 7.8-1. Study Participant Wearing Motion Capture Suit with Reflective Markers ....................... 42

Figure 7.9-1. Participant 001 with an Average Girth and Participant 006 with a Larger Girth ............. 44

Figure 7.11-1. Simple VEL Schematic ..................................................................................................... 49

Figure 7.13-1. Participant Postures while Performing Subtasks in Phase 1 ............................................. 51

Figure 7.14-1. Three Postures during LRU Transfer Subtask, Live Video, and Jack Software 

Animation ......................................................................................................................... 52

Figure 7.14-2. Example Output from Jack Software for Low Back Analysis .......................................... 53

Figure 7.14-3. Example Output from Jack Software for Static Strength Prediction ................................ 53

Figure 7.16-1. Pilot Phase PMD Topology .............................................................................................. 55

Figure 7.17-1. Example Webpages for PMD Search, Display, and Results Pages .................................. 56

List of Tables 

Table 6.5-1. Prioritized Task List Created following June 2012 Stakeholder Workshop ..................... 19

Table 6.5-2. Example Functional Breakdown based on Stakeholder Prioritized Tasks........................ 19

Table 6.6-1. Motion Segmentation and Database Fields Worksheet .................................................... 30

Table 6.7-1. Study Risk Ratings (Higher # => Greater Risk) ............................................................... 33

Table 7.3-1. Options for Data Storage for 26 Gigabits ......................................................................... 37

Table 7.9-1. Example Task Breakdown Worksheet with Segment Times and Descriptions ................ 45

Table 7.9-2. User’s Guide for Database ................................................................................................ 46
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1.0 Notification and Authorization 

Dr. Cynthia Null, NASA Technical Fellow for Human Factors at the NASA Ames Research 

Center, was selected to lead this assessment. The task request (TI-12-00774) was approved for 

the Marshall Space Flight Center (MSFC) Systems Analysis Branch human factors engineering 

organization on April 30, 2012. Phase 1 was initiated by the MSFC contractor team in 

October 2012 and delivered in February 2013. Phase 2 was approved through the MSFC 

Technical Excellence Program in April 2013, with continuing NESC oversight. Work was 

initiated by the MSFC contractor team in April 2013 and delivered in September 2013. 

The key stakeholders identified for this assessment are representatives from the three major 

human spaceflight programs, a modeling and simulation working group, and the Office of 

Primary Responsibility for the NASA Space Flight Human System Standard (SFHSS), 

NASA-STD-3001 Volume 2, and the Human Integration Design Handbook: 

• Ground Systems and Operations Program: Dr. Gena Henderson, Chief, Integration 

Branch/System Engineering and Integration Division, Kennedy Space Center 

• Space Launch Systems (SLS) Program: Ms. Sally Richardson, Human Factors Engineer, 

Systems Analysis Branch, MSFC 

• Multi-Purpose Crew Vehicle (MPCV) Program: Ms. Susan Baggerman, Health and 

Medical Technical Authority, Space Life Sciences Directorate, Johnson Space Center 

(JSC) 

• NASA Integrated Model Architecture Working Group: Mr. Joe Hale, Systems Engineer, 

Systems Engineering Management Office, MSFC 

• NASA SFHSS, NASA-STD-3001 Volume 2, Section 13.0, ground support operations 

sections: Jonathan Dory, Chief, Habitability and Human Factors Branch, JSC 

• MSFC Technical Excellence Program 
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2.0 Signature Page 

Submitted by: 

Dr. Cynthia H. Null Date 

Significant Contributors: 

Dr. Mariea Dunn Jackson Date Mr. Trey Perry Date 

Mr. Jason C. Quick Date Mr. Jack W. Stokes Date 

Signatories declare the findings, observations, and NESC recommendations compiled in the 

report are factually based from data extracted from program/project documents, contractor 

reports, and open literature, and/or generated from independently conducted tests, analyses, and 

inspections. 

Team Signature Page on File - 4/25/14
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3.0 Team List 

Name Discipline Organization 

Core Team 

Cynthia Null Lead ARC

Charles Dischinger Deputy Lead MSFC

Mariea Dunn Jackson Project Lead MSFC

Trey Perry Simulation Engineer MSFC

Jack Stokes

Human Factors Subject Matter Expert 

(SME) MSFC

Jason Quick Human Factors SME MSFC

Victoria Garcia Simulation Engineer MSFC

Caitlyn Durham Simulation Engineer MSFC

Marlin Williamson Simulation Engineer MSFC

Advisory Board 

Tim Barth Systems/Human Factors Engineer

Systems Engineering Office 

(KSC)

Barbara Kanki Maintenance SME ARC

Katrina Stelges Industrial/Human Factors Engineer United Space Alliance (KSC)

Sudhakar Rajulu

Anthropometry and Biomechanics 

(Physical Ergonomics) SME JSC

Damon Stambolian Ground Processing SME KSC

Gena Henderson

Chief, Integration Branch/System 

Engineering and Integration Division KSC

Robert Humeniuk Simulation Engineer KSC

Fayssal Safie

Reliability and Maintainability 

Engineering Technical Fellow

NASA Safety Center 

(NSC/MSFC)

Brad Lawrence Motion Capture SME United Space Alliance (KSC)

Ben Vanlear GSE Design GRC

Sally Richardson Level II Systems Integration MSFC

Chris Johansen MTSO Program Analyst LaRC

Administrative Support 

Diane Sarrazin Project Coordinator LaRC/AMA

Linda Burgess Planning and Control Analyst LaRC/AMA

Christina Williams Technical Writer LaRC/AMA
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3.1 Acknowledgements 

The team acknowledges the assistance of Mr. Steven Gentz, NESC Chief Engineer at MSFC, for 

valuable guidance in completing this work. The team also acknowledges those who volunteered 

their time to serve as participants in the motion capture sessions. 
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4.0 Executive Summary 

The scope of this assessment was to develop a library of basic 1-Gravity (G) human posture and 

motion elements used to construct complex virtual simulations of ground processing and 

maintenance tasks for spaceflight vehicles, including launch vehicles, crewed spacecraft, robotic 

spacecraft, satellites, and other payloads. 

The report herein describes the task, its purpose, performance, findings, NASA Engineering and 

Safety Center (NESC) recommendations, and conclusions in the definition and assemblage of the 

postures and motions database (PMD). The primary project goal was to support the human 

factors design and analysis work being done on future spaceflight vehicles, ground systems, 

ground support equipment (GSE), and ground processing worksites. 

4.1 Background 

The use of computer-aided design (CAD) environment modeling, integrated with human 

anthropometric and performance modeling, offers assessment techniques previously lacking 

without the construction and maintenance of full-scale 1-G physical mockups. NASA has the 

potential to conserve program resources by increasing use of virtual technology for developing 

requirements, design concepts, and operational procedures for ground processing of spaceflight 

vehicles. As part of a risk mitigation exercise, the NESC requested the creation of a library of 

virtual human postures (e.g., body positions or poses) and simple motions for CAD-based human 

models for use in a worksite task evaluation [ref. 1]. 

Since the design, development, and ground processing of spaceflight vehicles occurs across 

multiple NASA centers and contractor sites, a collaborative effort was established by the NESC. 

Operability studies conducted by the Kennedy Space Center (KSC) Ground Systems 

Development and Operations (GSDO) Program defined the human activity at the element 

(primitive) level, with the potential for linking motion and posture elements for task procedures. 

A subsequent assessment conducted by the Marshall Space Flight Center (MSFC) team 

addressed two previously known challenges: combining human body postures or motions via 

stringing sequences of elements into credible chains of performance activities, and accounting 

for mass handled in a 1-G environment [ref. 2]. 

This assessment was provided with two distinct project phases and corresponding task orders. 

Phase 1 was funded by the NESC from October 2012 through March 2013, and Phase 2 was 

funded by the MSFC Technical Excellence Program from April 2013 to September 2013. 

4.2 Approach 

In developing the PMD, the overarching project goal was to support the human factors design 

and analysis work being done on future spaceflight vehicles, ground systems, GSE, and ground 

processing worksites. Currently, assessing tasks with digital human modeling (DHM) software 

can be labor-intensive and produce results that minimally account for human behaviors and 
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anthropometric variability. The intent of the PMD database is to provide sufficient element data 

for a knowledgeable DHM software user to construct realistic task simulations using 5th and 95th

percentile human avatars, motion capture data, and imported CAD environments of spaceflight 

vehicles. 

The MSFC assessment was considered a pilot study in scope with data collected to prove the 

database concept and validate the virtual simulation technique. Function-level activities were 

chosen from a prioritized list generated by project stakeholders, then deconstructed to the task, 

subtask and element levels. Scripts were created at the subtask level and participants performed 

the activities by interacting with low-fidelity physical mockups while data was collected using a 

motion capture system. A library of motion and posture elements was developed for Jack1

software users. The library permits searching and grouping of elements (e.g., postures or 

motions) that support user analysis and design. Once the desired element has been identified, the 

user can access the corresponding data package containing images, video, analysis, and Jack 

motion files to aid their design work. Linked elements can represent conceptual procedural tasks 

in the ground processing environment, which may result in a more effective design, 

development, and verification and validation approach. 

The MSFC study was conducted in two phases: Phase 1 developed an operations process and 

initial database design, and Phase 2 refined the initial effort into a more comprehensive database. 

Phase 1 was successful in conducting background research and establishing processes to begin a 

pilot study. Emphasis was placed on defining the study scope, developing baseline operating 

procedures, and conducting the pilot study to obtain a representative data sample for the 

demonstration database. This foundational work enabled Phase 2 to refine the processes 

developed in Phase 1 and to focus on improving the quality and quantity of data collected. 

Changes in the technical approach between Phase 1 and Phase 2 are discussed in the appropriate 

sections. 

4.3 Results 

Participant trials defined capabilities of the Jack software for simulations, proved the ability to 

integrate CAD environments and motion data into the software virtual environment with human 

models (or avatars), and populated the pilot database with useful data to support design and 

analysis work. 

The number and configuration of Virtual Environments Laboratory (VEL) motion capture 

cameras was sufficient to cover most motion capture needs using various mockup techniques. 

While plywood and polyvinyl chloride (PVC) mockups were used extensively in Phase 1, their 

physical surface area sometimes caused markers on the motion capture suits to become obscured 

 

1

Jack software is a three-dimensional (3-D) interactive ergonomics and human factors CAD package developed by 

the University of Pennsylvania’s Center for Human Modeling and Simulation. Jack is maintained and distributed by 

Siemens Product Lifecycle Management Software.
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from the view of near-infrared cameras. In Phase 2, it was found that using more wireframe 

style mockups resulted in less marker obstruction, which resulted in lower data post-processing 

time. Potential benefits to upgrading the VEL’s current camera configuration (e.g., enabling 

higher resolutions and decreasing light sensitivity) are addressed in Section 7.0. 

VEL personnel segmented capture session videos and three-dimensional (3-D) motion data into 

subtasks and elements, while experiencing challenges defining start/stop points because of 

participants’ unique actions and transitions. Data was provided to the database design team as 

compressed data packets were processed and uploaded to the library. 

The database website provides the ability for Jack software users to search for elements based on 

keywords and participant/avatar attributes. The dynamic webpages were built using the 

Macintosh-Apache-MySQL-PHP (MAMP) development package hosted on a MSFC server. 

The pilot database provided a sample of useful, generalized motion data that can be downloaded 

as organized data packets (.zip files). The MSFC server is accessible while on-site or through 

virtual private network (VPN) connection for offsite users. 

4.4 Forward Work 

This study provided simplified posture and motion elements and task variations and 

demonstrated the intended use of a motion capture database. Proposed future efforts are as 

follows: 

• Make the database available to projects and programs for design analysis. 

• Collect more data to expand the database. 

• Improve the technology used in motion capture sessions to integrate hand tracking and 

head-mounted displays to observe manual dexterity and allow participants to experience 

immersion in the virtual environment. 

• Integrate hand tracking and head-mounted display into motion capture sessions to 

observe manual dexterity, observe immersion experience, and increase simulation 

fidelity. 
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5.0 Assessment Plan 

The NESC-initiated project proposed creation of a library of human postures and motion 

sequences that enabled realistic virtual simulations of 1-G ground processing and maintenance 

tasks. Based on a prioritized task list, a study was designed to capture scripted motion sequences 

performed by participants in an operational motion capture and human modeling laboratory. 

Data was to be stored in the PMD that would be available to NASA, its contractors, and 

commercial partners. The MSFC contractor team was to perform the task simulation sessions, 

database development, and report generation. The NASA civil servants provided oversight. 

The majority of the assessment plan was followed based on the pilot study project scope defined 

by the MSFC contractor team. The effort was comprised of two phases, with Phase 1 identifying 

acceptable laboratory operations, realistic task simulations, data processing and database/ 

interface design. The emphasis remained on data collection that enabled creating subtask 

animations linked for avatar simulations within a 3-D CAD virtual environment. Phase 2 refined 

the data collection and post-processing techniques. Phase 2 also provided an opportunity for 

additional unique task simulations, resulting in new element data collection and an expanded 

database library. 

Differences between the study initial plan and execution represent decisions reached in 

coordination with the stakeholders, user community, and team members to refine the initial 

concept while maintaining a useful design product within program constraints. Major 

differences between the initial plan and execution were: 

• Analysis and data collection planning in Phase 1 began 4 months later than expected 

because of contractual adjustments. Phase 2 started 2 months later than expected because 

of personnel and funding changes. 

• Collaborative postures and motions creation between MSFC and KSC was minimal and 

consisted of feedback on initial session scripts and final stages of database development. 

• The human motion data collection was limited to an amount that validated the virtual 

simulation techniques and database design.

• Stakeholders provided a prioritized list of functions and tasks. For the pilot study scope, 

representative task portions were chosen to capture a subset of high-priority activity.

• In cases where definition was not provided for KSC-specific worksites, ground 

processing equipment, or activities, the VEL team created low-fidelity mockup hardware 

of approximate dimensions based on anticipated launch vehicle configurations.

• Pre-study assessment demonstrated the need to have transparent or translucent mockups 

to allow the data cameras to track the test subject suit markers.
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• Operational constraints for pre-launch processing activities were further captured relative 

to body motions (e.g., twisting, leaning, stretching, etc.) beyond what was obtained in 

Phase 1. 

• Relatively realistic mass was introduced into some task simulations to challenge the 

human operator in performing pre-launch simulated motions. 

6.0 Problem Definition, System Requirements, and Implementation 

6.1 Problem Definition 

The goal of this study was to define and create a digital library of human model postures and 

motion elements (i.e., primitives) that captured basic, measurable, and accurate human behavior 

motions. Database products should provide the capability for human factors analysts to link 

postures and/or motion capture sequences to simulate more complex ground processing subtasks 

for spaceflight vehicles. This will offer Jack software users a source of application specific 

human data with unique behaviors and movements and minimize the need to estimate manikin 

postures and motions. 

The digital library was intended to be a design tool for: 1) space vehicle ground processing 

worksite design concepts and trades; 2) design development; 3) requirements establishment, 

analysis, verification, and validation; 4) safety and quality assurance assessment; and 5) real-time 

procedures preparation for imminent processing and maintenance tasks. As virtual humansystem simulation is becoming an effective method for human factors engineering assessments, 

the use of CAD environment modeling, integrated with human anthropometric and performance 

modeling, offers techniques for capturing human behaviors previously lacking without full-scale 

1-G physical mockups. 

Modeling human performance is still a challenge utilizing CAD modeling techniques, even for 

performing simple tasks, including human body postures or motions. As previously mentioned, 

there are difficulties in stringing sequences of virtual postures and motions into credible chains 

of performance activities; and there is difficulty in accounting for mass handled in a 1-G 

environment [ref. 2]. However, NASA is interested in using such virtual technology to address 

design concepts and requirements definition, and operational procedures for ground-based 

spaceflight vehicles. Hence, an integrated effort was established among the NESC, KSC, 

Johnson Space Center (JSC), Glenn Research Center, and MSFC to create a library of elements 

(primitives) representing human postures and motions, which can be recognized and utilized in a 

CAD modeling environment. By developing libraries of common validated ground processing 

actions, pre-launch processing tasks can be modeled based on the library elements, offering 

insight to engineering, safety and quality assurance, preflight operations organizations, and 

program management. This use of digital design for pre-launch processing has the potential to 

decrease the likelihood of redesign and improve design for operability for NASA programs. 
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6.2 Scope and System Features 

This study was a two-phase pilot study supporting best practices for continued motion capture 

and database efforts. The study defined a database containing specific human postures and 

motions that can be downloaded and assembled in a “chain” to replicate a ground processing 

procedure. It was scoped as a pilot study for proof-of-concept only, with intentions of proving 

the concept of a virtual library of postures and motions. 

• The primary customers and users of the PMD will be engineering/design, safety and 

quality assurance, and ground processing and engineering organizations. 

• Data collection was conducted by MSFC using its VEL tool for collecting virtual data 

and transposing it into a library of human posture and motion elements. 

• The PMD consisted of tabulated data of elemental postures and motions, including 

appropriate anthropometric data. 

• Data is accessible to the user for linking (chaining) to create virtual animations of typical 

launch processing procedures. 

Desired Features 

The initial functionality desired for the PMD was based on existing NASA-hosted websites that 

store, search, and retrieve data. Features included: 

• Front-end, web-based data interface 

• Secure permission-based data entry 

• Pull-down menus 

• Ability to add custom text 

• Links to images, documents, 3-D models, videos, and raw motion data 

• Searchable user application 

• Simple navigation 

• Multiple data windows for comparison of human tasks, anthropometric categories, and 

cross-relationships 

• Ability to create custom reports with imagery 
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6.3 Ground Rules and Assumptions 

The following ground rules and assumptions were imposed for the Phase 1 and 2 study: 

1. Constraints were imposed on each posture or motion when the load exposed to the human 

motion capture participant might exceed safe performance limits. 

2. For the pilot phase, Jack software was used to create simulation data. 

3. The pilot phase database was intended to support the work of designers and analysts 

addressing human actions in ground processing operations. 

4. The motion analysis database was elemental and generic and not tied to a specific 

worksite environment or ground processing functions. 

5. A typical pre-launch processing or maintenance task was defined by separating the 

activity into finite and measurable subtasks, which were reduced to strings of elements 

(primitives). These elements were the selectable items in the motion analysis database 

and can be linked in any order to create a task. 

6. Participants selected for the pilot study were limited to body and limb dimensions 

approximating the standardized 1988 Army Anthropometric Survey (ANSUR) 5th and 

95th percentile dimensions [ref. 8] as closely as possible (i.e., + 5 percent for Phase 2). 

7. The study was designed under ground rules and assumptions for lifting limits for standard 

tasks, to support the Ames Research Center (ARC) Human Research Institutional Review 

Board (IRB) recommended practices for assuring participant safety [ref. 3]. 

8. As a consequence of time and manpower constraints, the National Institute for 

Occupational Safety and Health (NIOSH) lifting equation calculations were performed 

using the calculations embedded in the Jack software rather than manually. The library 

user will need to make such calculations as their subsequent task is defined. 

9. Tasks to be modeled were based on stakeholder needs as defined in a prioritized list 

(see Table 6.5-1). Based on stakeholder recommendations for the pilot study, typical 

subtasks were selected which were generic in nature and could be representative tasks for 

various missions. These included hatch removal and temporary restraint, hatch entry, 

protective cover installation/removal, electrical connector management, and line 

replaceable unit (LRU) installation in standing and kneeling body positions. 

10. Subtask definition is enhanced if lower back analysis and static strength prediction are 

included. 

11. Task analysis toolkit within the Jack software is used in lieu of manual NIOSH lifting 

equation calculations. 
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6.4 Operational Definitions

Each function encompasses a set of tasks that were segmented into a series of subtasks 

(motions). Subtasks were reduced to their “element” parts, which included static postures and 

short, basic motions as shown in Figure 6.4-1. 

FUNCTION – Requested prioritized pre-launch processing activity (e.g., crew access arm 

ingress/egress), which contains several tasks. 

TASK – Measureable portion of functional activity defined by specific beginning and end points. 

Characterized by definable stopping or break points. Combination of tasks is equivalent to a 

function, which contains several subtasks. 

SUBTASK – Portion of a task which captures one or more postures or motions necessary to 

complete the least measurable activity portion of a task. One or more sequences of motions or 

postures are equivalent to and represent a subtask. Contains several posture and motion 

elements. 

ELEMENT – A posture, motion, or combination thereof, with a start and end point recognizable 

by the Jack software. Definable as a single standard entity in the PMD. 

PARTICIPANT – 5th percentile human female or 95th percentile human male wearing a motion 

analysis suit with critically placed reflective data-producing dots posing in a posture or moving 

in some definable and limited manner to replicate desired avatar motion. Participants are 5th

percentile female or 95th percentile male in stature and reach based on the 1988 ANSUR 

percentile definition [ref.8]. 

Figure 6.4-1. Operational Levels Defined for Motion Capture Planning and Database Content 

(Additional operational descriptions in Appendices)
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6.5 Technical Implementation 

The study required three main technical capabilities: assessment of human factors guidelines and 

task design for study; planning, capture, and processing of motion-related participant data; and 

the library design, development and implementation. Extensive learning and prototyping was 

necessary for each capability to produce favorable results. The study approach was built on 

existing knowledge of ground processing tasks, VEL motion capture capabilities, and current 

NASA database examples with an emphasis on the experience a designer or analyst would have 

using the database. 

Major efforts during the study included: 

1. Determining the highest-priority ground processing functions and related tasks, as 

specified by results from the stakeholder team workshop (Table 6.5-1). 

2. Defining representative subtasks found in more than one high-priority functions. 

3. Designing the experiment with participant simulation script and appropriate capture 

facility. 

4. Capturing subtasks as 3-D motion data for storage and retrieval. 

5. Reducing subtasks to their elemental motions and postures. 

6. Designing, building, and hosting database of elements. 

7. Creating functional, intuitive webpages to provide database content. 

8. Demonstrating how element database would be utilized by stakeholder community. 

Function Definition 

Two common function-level activities were chosen from a stakeholder prioritized list as shown 

in Table 6.5-1. The functions included the installation and/or removal of a typical launch vehicle 

access hatch and the installation of typical LRUs approximating a mass of 15 pounds with 

passage through the open hatch. Each function encompassed a set of tasks that were segmented 

into a series of subtasks (motions) as shown in Table 6.5-2. Subtasks were reduced to their 

“element” parts, which included static postures and short, basic motions. For relationships 

between function, task, subtask, and element see Figure 6.4-1 and for a more detailed description 

see Appendix A. 
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Table 6.5-1. Prioritized Task List Created following June 2012 Stakeholder Workshop 

Table 6.5-2. Example Functional Breakdown based on Stakeholder Prioritized Tasks 

Original document: Task Descriptions for Motion Analysis B (version 1).xlsx 

User Scenario and Interface Concepts 

The process of assessing tasks with digital human models can be labor-intensive and produce 

inaccurate results. Software users are required to manually position the participant in predicted 
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key postures and then direct the software to interpolate movements. It can be difficult to 

accurately depict motions because of human behaviors and anthropometric variability. 

As envisioned, the database would be populated with element data and provide sufficient 

information for a knowledgeable Jack software user to manipulate 5th and 95th percentile human 

avatars within an imported, CAD-modeled environment of a spaceflight vehicle. The user would 

access the database, search for key motions and postures envisioned in the subtask, and link 

selected elements into subtask motions and activities. After correcting for overlaps and conflicts, 

the user would document the final virtual simulation of a specified ground processing operation. 

Preliminary webpage mockups were created in Adobe Illustrator to communicate the site 

structure and user experience. Concepts identified the ability to select keywords for postures and 

motions, and tasks and subtasks. Human operator (i.e., study participant) characteristics could be 

selected to narrow searches. The results page would show thumbnail images and appropriate 

description of specific elements and element detail pages would provide information per element 

and the ability to download a data packet. Figures 6.5-1 through 6.5-3 and Appendix H show 

concept visuals. 

Figure 6.5-1. Initial Mockup of Database Search Page 
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Figure 6.5-2. Initial Mockups of Database Results Pages 

Figure 6.5-3. Concepts for Website Flow and Objectives 

6.6 Motion Capture Sessions 

All motion capture sessions were conducted in the MSFC VEL utilizing a combination of civil 

servant and contractor participants. Scripted subtask postures and motions were performed in 

Graphical User Interface (GUI) CONCEPTS 

Start: search inputs Select: Element results list 

Download: Element data overview Element data details 

Search returns set of 

images referencing 

individual elements 

Download some or 

all data associated 

with an element 
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several mockup configurations while near-infrared cameras captured the 3-D motion data. Realtime video of the participant performance and their comments were recorded. 

In post-processing, the VEL team segmented data into logical elements based on natural and 

scripted pauses in participant motions. The database was developed for Jack software users to 

search for elements that support their analysis and design work and where data packages 

containing images, video, analysis, and Jack motion files can be downloaded. 

Participants 

Desired participant measurements were drawn from the 1988 ANSUR database of body 

dimensions to provide a representative sample that met requirements for accommodating ground 

operations personnel of different sizes. In Phase 1, the participant pool was a convenience 

sample drawn from MSFC civil servants and contractor team members: three males 

approximating 95th percentile in height and reach and two females approximating 5th percentile 

in height and reach. Recruiting was accomplished with direct invitation, team referrals, word-ofmouth, announcements in the Marshall Star newsletter, and MSFC’s Knowledge Now social 

network. The number of participants was capped at five to meet anthropometric requirements 

and provide sufficient example data while allowing time for data post-processing. For Phase 2, 

the participant pool was drawn mostly from summer interns (contractors), with only one MSFC 

civil servant/contractor participant. As in Phase 1, Phase 2 limited the number of participants to 

five, with three 95th percentile males and two 5th percentile females. Unfortunately, because of 

participant and VEL team availability, one of the 5th percentile females was not able to be 

included in the study. Therefore, the 5th percentile female data in Phase 2 came from a single 

participant. An example of a participant session is shown in Figure 6.6-1. 

 

Figure 6.6-1. Study Participant in Motion Capture Suit and Cap with Reflective Markers; Researcher 

taking Anthropometric Measurements 

Note: The participant’s face is masked to retain anonymity. 
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Study Protocol 

Scripted procedures were created in compliance with the ARC Human Research IRB 

recommended practices. The procedures were reviewed by the MSFC Institutional Health (IH) 

organization to assure participant safety, health, and proper treatment during the study. Selected 

participants, after being assessed for appropriate physical condition and proven balance skills, 

were provided training for proper lifting technique as certified by the IH organization. 

During capture sessions, team members positioned participant body markers and recorded 

participant anthropometrics. They assessed physical capabilities and existing knowledge about 

ground processing tasks and participants completed a demographics/work experience form. 

Participants with limited ground processing knowledge were provided with supplemental 

training on the spacecraft vehicle worksite, task goals, and additional time for rehearsing 

subtasks. 

Participants performed the motion sequences according to scripts and were encouraged to focus 

on the task and subtask completion goals rather than strict methods for completion (see examples 

of participants during session procedures in Figures 6.6-2 through 6.6-5). The sessions were 

completed with participants providing subjective feedback on task comfort and research 

practices, which complemented the motion data and researcher observations. Participant 

information remained confidential and identifiable information was not provided in published 

data. See Appendix C for more details on session procedures. 

 

Figure 6.6-2. Mockup and Video Configurations during Motion Capture Study at MSFC VEL 

Note: The participant’s face is masked to retain anonymity. 
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Figure 6.6-3. Camera Mounting Structure and Workspace at MSFC VEL 

Figure 6.6-4. Vehicle Hatches, GSE Shelf and Platform, Battery LRU Mockups used during 

Phase 1 
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Figure 6.6-5. Sample Mockup Configurations with Participants Performing Subtasks during 

Phase 1 

Note: The participant’s face is masked to retain anonymity. 

Mockup Fidelity 

For Phase 1, team members created mockups of generalized vehicle hatches and GSE shelves. 

Phase 2 included improved fidelity versions of the Phase 1 mockups, plus additional mockups 

utilized for addressing increased element capture. Also included was a part-task wireframe 

mockup representing a segment of a launch stage that included a wireframe hatch; a connector 

plate with cabled connectors accessed through an access port; and protection covers over several 

connection locations protruding at different heights. 

The environment and equipment were represented by low-fidelity mockup hardware of 

approximate dimensions as would typically be used for spaceflight vehicles and worksites. Prestudy assessment was restricted by the number of data cameras and demonstrated the need for 

transparent or wireframe mockups to adequately track the participant suit markers throughout the 

motion. Figures 6.6-6 and 6.6-7 show a hatch mockup progression from solid-surface plywood 

to transparent acrylic, to a “wireframe” PVC, and to a wireframe steel rod with custom-connector 

system. 
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Figure 6.6-6. Progression from Solid-surface Plywood to Wireframe Steel Rod Hatch Mockups 

Figure 6.6-7. Phase 2 Worksite Mockup Constructed with Steel Rod and Multi-insertion Connector 

System 

To further address the customer prioritized task list (Table 6.5-1) and expand the database with 

additional element creation, the Phase 2 effort generated mockups that improved the participant 
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interactions and data capture quality. The mockups received amendments and corrections, while 

generic motions used in pre-launch processing indicated a need for more LRU and utility actions, 

including locating these units in various postures and mating/demating connectors clustered in 

typical limited access locations. Solid low-fidelity mockups and wireframe mockups were used 

to gather this new data. Extensive development of a steel rod and a multi-insertion connector 

system allowed the VEL team to rapidly create accurate, transparent, and customized mockups. 

Plastic, large-mesh netting was used to provide participants with the context of solid surfaces 

while allowing reflective joint markers to be tracked and unobstructed video to be captured. See 

Appendix B for more detailed information on mockup configuration. 

VEL Motion Capture 

The MSFC VEL is equipped and calibrated with 16 near-infrared motion capture cameras that 

track markers strategically placed on a participant’s body in a 3-D space. The cameras work in 

conjunction with Cortex software. This software is primarily used for motion tracking and 

creating templates that define a human or prop. Software for Interactive Musculoskeletal 

Modeling (SIMM) is an add-on to the Cortex software that creates a skeleton based on the 

human marker data, and calculated skeleton bone are used for human factors engineering 

analysis. Jack software was used to record the motion channelsets of avatars from the Cortex 

software (Figure 6.6-8). Details are provided in Appendix D. 

Figure 6.6-8. Progression from Human Participant with Reflective Markers, to Motion Analysis Joint 

Location Data, to Steps for Cortex Software Skeleton, to Jack Software Avatar Model 

Two high-definition video cameras and supporting software programs were used in the study. 

Prior to the PMD study, the capabilities of VEL focused mainly on a body in 3-D space. The 
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purpose of most motion recording sessions in Phase 1 was to create templates for a specific 

participant, not for playback of recorded motions. During Phase 2, a new template process was 

used where a default template, created from a single detailed range of motion (ROM) capture, 

was applied to all participants using a tool in the Cortex software that adjusted the template to fit 

each participant individually. This study required a significant effort to develop best practices 

for creating motion playbacks with recorded data in DHM software. See Appendix D for 

additional details. 

Figure 6.6-9 shows a work breakdown of the approach to creating data necessary for the PMD. 

The work breakdown scope included the activities directly associated with motion capture 

recording and Jack software outputs. Work activities not included in the figure include 

anthropometric measurements, suit fitting/reflective marker application, task introductions, 

briefing, consent forms, safety procedures, questionnaires, demographics records, live pictures, 

and debriefing. Activities outlined in Figure 6.6-9 are described in Section 7.0. 
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Figure 6.6-9. VEL Work Breakdown Approach 

Data Planning and Organization 

The organization of data file types include file nomenclature, folder structure guided capture 

session planning, database design, data processing, and database population. Table 6.6-1 shows 

the master spreadsheet used to coordinate between team members responsible for human factors, 

experiment design, data processing, and database design. See Appendix E for additional 

spreadsheet details and Appendix B for subtask examples. 
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Table 6.6-1. Motion Segmentation and Database Fields Worksheet 

Motion capture data, video, and supporting data were processed, organized into folders, and 

shared as compressed (zipped) files for database inclusion, as shown in Figure 6.6-10. From the 

PMD, Jack software users can access the zipped files associated with a task, which include four 

folders for each subtask. A Media folder houses reference images, while the library analysis 

material is located in the Data folder. The Environment folder contains environment files from 

which channelset motions can be assembled into a virtual simulation. Posture files are preloaded 

in the Environment folder. The Jack figure resides in the Environment folder and can be opened 

with associated postures linked for task assessments. 
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Figure 6.6-10. File Naming Conventions and Folder Structure of Downloadable .zip Data Packets 

Database Design and Development 

The team explored search and download techniques that would make the various types of data 

easily understood and retrievable by the user. Emphasis was placed on supporting the users with 

an intuitive, functional database. 

Reference lists that show entered functions, tasks, and subtasks may be found on the 

corresponding pages on the PMD website. The element page contains a list of all elements and 

their respective task and subtask. This page is where Jack software users are able to download 

the compressed packets. The search page allows users to perform keyword searches using 

combinations of tasks, subtasks, specific postures and motions, and anthropometric constraints. 

Finally, the anthropometric page serves as a reference list for participant anthropometric 

measurements and contains descriptions of the different anthropometric measurements of 

concern based on the 1988 ANSUR study. 
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See Appendix G for additional technical details on database structure and Section 7.0 for 

additional webpage design details.

6.7 Risk Assessment 

There are potentially inherent risks in performing any simulations using human test subjects. 

Additionally, potential for failure can occur in the simulation and data collection design relative 

to desired and purported goals and accomplishments. This section assesses risk relative to 

defining realistic elements for virtual procedures assembly, and credible PMD elements capable 

of being assembled into meaningful spaceflight vehicle ground operations. 

The design and operational risks inherent in this study were assessed according to the NASA 

Program Risk Scoreboard. 

Risks during this study included: 

A. Having realistic and useful motion capture data in the database (LR-1, meaning level of 

risk rated as 1). 

B. Defining measureable and specific motions and postures to a database user (LR-2). 

C. Delivering a database that is accessible and user-friendly (LR-5). 

D. Providing a set of data to: develop concepts, assess safety and quality assurance designs; 

serve as a human factors engineering tool; and provide sufficient detail to create and 

modify defined operations (LR-2). 

E. Study design that is protective of study participants (LR-1). 

F. Processed data that is “clean” and accurately represents the realistic and useful motion 

data captured (LR-2). 

By applying the NASA Program Risk Scoreboard to this study, the following was determined. 

No combination of risk likelihood and consequences could reach a conclusion that any of the 

identified risks would invalidate the simulation or adversely impact the avatar element data 

within the PMD. Items A, B, D, E, and F carried to a worst-case consequence of “5” will only 

reach a cautionary “yellow” rating, indicating minor impact to program operations or critical 

hardware. This is based on likelihood of occurrence while recognizing consequences. However, 

item C likelihood risk was deemed significantly higher, with a rating of “4” for a likelihood of 

occurrence and a “4” as the consequence impact producing a combined rating of 23 thereby 

placing it potentially in the red zone. The worst-case combination could result in the user 

community not being able to access and utilize the program in a timely manner, thereby 

impacting their program milestones. Though current plans permit users outside the MSFC 

firewall to access the database, it will require significant user coordination, approval, and 

certification. An alternate solution to improve study risk is to create a public domain server 

(virtual or physical) available through a formal process to dedicated government and contractor 

users within the restrictions of NASA Information Technology (IT) security. 
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6.7.1 Detailed Risk Descriptions and Mitigation Results 

The NASA Program Risk Scoreboard was applied resulting in the assessment ratings shown in 

Table 6.7-1 (see Appendix F for NASA Program Risk Scorecard and Ratings Table). 

Table 6.7-1. Study Risk Ratings (Higher # => Greater Risk) 

A Useful Motion Capture Data LR-1 L/C: 1/5 = 12 (Y) 

B Measureable and Specific Motions and Postures LR-2 L/C: 2/4 = 14 (Y) 

C User-Friendly and Accessible Database LR-5 L/C: 5/4 = 23 (R) 

D Program Design Supportive Data LR-2 L/C: 2/5 = 17 (Y) 

E Study Participant Protections LR-1 L/C: 1/5 = 12 (Y) 

F Clean Post-Processed Data LR-2 L/C: 2/4 = 14 (Y) 

A. Useful Motion Capture Data - Data Storage and Hosting Capabilities

Minimal likelihood; highly significant consequences – Proven VEL expertise in human capture 

and modeling capabilities and creative data-gathering techniques. 

• Challenge is converting physical mockup session data with human subtask actions into 

virtual, elemental avatar motions and postures. Successful demonstration was 

accomplished. 

• Challenge is the ability to link motion elements and separating subtask performance into 

elements. Successful demonstration was accomplished. 

B. Measureable and Specific Motions and Postures 

Low risk likelihood; significant consequences – Human factors expertise utilizing 1988 ANSU 

anthropometric data as a standard and successfully finding test participants in close approximate 

range assured data was directly applicable to launch processing population. 

• Care taken in selecting closely approximate 5th and 95th percentile male and participants. 

• Element-level data collected met study protocol constraints (e.g., NIOSH, etc.) was 

generalizable for pre-launch processing worksite procedure generation; including 

participant safety concerns. 

• Functional PMD is usable by users meeting stakeholder requirements. 

C. User-Friendly and Accessible Database 

High likelihood; significant consequences – Concern with providing pilot study data to users in 

accordance with NASA IT security requirements. 
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• PMD is available to users in a MSFC restricted database and meets stakeholder funding 

and schedule requirements. 

• Issue with accessing data by external user in accordance with NASA IT security 

constraints. 

• ‘Consequences’ rating is less than the maximum since qualified NASA IT security 

personnel can manually provide data to an approved external user. 

D. Program Design Supportive Data 

Low likelihood; significant consequences – PMD data when linked demonstrates the capability 

of creating subtask-level virtual activities with an avatar. 

• The VEL team demonstrated the concept of chaining elements, though refinement is 

needed to clear momentary breaks in the sequent elements. 

• Users who understand the chaining techniques can combine the elements in the database. 

Such assembled activities can be used in the design spectrum beginning with design 

concept and progressing through verification to pre-launch spaceflight vehicle 

processing. The technique can be used to develop concepts, assess safety and quality 

assurance designs; serve as a human factors engineering tool; and provide sufficient 

detail to create and modify defined operations. 

• The less than optimal risk rating was due to the data collected under a pilot study and 

significantly more database elements are needed for the database to reach its full 

potential. 

E. Study Participant Protections 

Minimal likelihood; highly significant consequences –Study was controlled from its beginning to 

meet Occupational Safety and Health Agency (OSHA) and NASA test subject restrictions within 

the study operational constraints. 

• Participant physiological concerns were defined with concerns about non-standard 

postures and movements, including moving weighted mockups. 

• Study operations protocol was approved by MSFC IH organization per IRB requirements 

as being acceptable for motion requirements. 

F. Clean Post-Processed Data 

Low likelihood; significant consequences –Final post-processed data should be “clean” (i.e., as 

few errors as possible) and the recorded motions should mirror the participant motions. Unclean 

data threatens the PMD integrity and introduces additional cost by adding additional post-process 

time and/or needing to perform another capture for the motion in question. 

• Video footage of participant sessions was retained to validate final post-processed data. 

• In Phase 2, a default template was used for participants that vastly reduced the chance of 

“unclean” data because of an improper ROM capture during template creation. 
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• In Phase 2, research was conducted on the default marker set used during motion capture 

sessions and improvements were made in problem areas (e.g., hand and head tracking). 

• Phase 2 employed post-processing techniques not performed in Phase 1, which allowed 

VEL operators to smooth shaky markers and to fill in gaps in marker data due to 

obstructions and/or un-identification. 

7.0 Data Analysis 

7.1 Overview 

Five trials with the five participants produced significant Phase 1 results including: defining 

capabilities of the Jack model for simulations; and the ability to combine CAD models and 

environments from Pro/ENGINEER into the Jack virtual environment with human models. Ten 

sessions in Phase 2 provided additional unique task motions to expand the database. 

The 16 data cameras in the VEL provided useful data during the pilot study, especially as 

mockups progressed from solid surfaces to open PVC structures and wireframe structures. 

However, more and/or upgraded (i.e., not light sensitive and higher resolution) cameras are 

needed with high-fidelity mockups to provide appropriate context for tasks. Stakeholders and 

VEL team members recommended a need for transparent and solid higher fidelity mockups. In 

Phase 2, wireframe mockups with steel rod and custom-designed connectors were developed to 

provide rapid fabrication capabilities, clean motion tracking, and more realistic context of the 

physical worksite for study participants. 

For initial participants, detailed video review by human factors SMEs provided segmentation to 

define start/stop points for each motion. VEL teammates created corresponding subtasks and 

elements from the 3-D motion data and processed video and motion data for subsequent 

participants. The segmentation proved challenging with variability in participant body 

movements and transitions between motions, but resolving these issues provided opportunities 

for team member collaboration. 

The PMD provides a sample of useful, generalized motion data. An ability to manipulate pilot 

study avatars will be necessary as Jack software users make corrections in hand/arm locations, 

widths, and mass lifting relative to simulate specific tasks and handled hardware. To support 

those new simulations, the VEL team needed to know the anticipated LRU dimensions and 

masses for the MPCV and the SLS launch vehicle. 

7.2 Database Review 

In the early learning and exploration phase, research on existing databases highlighted 

potentially useful features and limitations. The University of Michigan Center for Ergonomics 

has an accomplished Human Motion Simulation group that offers access to their data. However, 

while they have information on motion files and documentation for each experiment, they do not 
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have an organized database that could be analyzed for search techniques or data storage methods 

to support the PMD design. 

Internal to NASA, the NASA Imagery Reporting Database was a recent example of a simple 

search interface for a large amount of data and much of the page layout, data display, and site 

flow were applicable to the PMD. However, after an extended effort to gain access to the source 

files, the PMD team decided to build a new, simple database to avoid complications with code 

that would need to be modified or removed. 

Additional projects and websites that could be reviewed during future efforts include: 

• Resources for the entertainment industry 

(e.g., Mixamo http://www.mixamo.com/motions ) 

• University-hosted databases (e.g., Carnegie Mellon’s http://mocap.cs.cmu.edu/) 

• Government-sponsored projects (e.g., Virtual Soldier Research 

http://www.ccad.uiowa.edu/vsr/) 

7.3 Site Hosting and IT Security 

Methods for organizing, storing, hosting, and accessing data were researched to provide simple, 

intuitive PMD access. NASA-shared, MSFC, and internal team servers and cloud network 

services were compared for cost, ease of support, and time to implement. Existing databases and 

hosting services were studied for desired functionality and technical implementation 

requirements. Table 7.3-1 shows the estimates provided for a November 2012 project status

[ref. 4]. 
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Table 7.3-1. Options for Data Storage for 26 Gigabits 

Following these estimates, the team pursued funding for MSFC server space to host an Agencyaccessible database that utilizes an authentication system developed by the database team to 

validate approved user access. This proved immediately challenging because of program 

constraints and was not resolved during the pilot phase. To optimize project results and 

maximize team member contributions creating the database, the requirements for database 

hosting were limited to an MSFC server that was only accessible inside the Center security 

firewall (i.e., onsite users). Access to the database from off-site is possible using MSFC VPN 

access. 

For future work, the PMD security plan is the Distributed Engineering Collaborative Information 

System CD-9999-M-MSF-2722 (i.e., ITSP 2722). See Appendix G for additional technical 

information on the software tools used and the underlying database structure. 

7.4 GSDO Program Initial Baseline Work 

The GSDO Program initiated a timeline analysis to improve the processing flow of ground 

systems-interfacing spacecraft, including the Orion MPCV spacecraft and SLS. To develop the 

analysis, it was determined human activity must be defined at the element (primitive) level to 

create processing functions from functional subtask segments. An initial effort produced in the 

KSC Human Engineering Modeling and Performance (HEMAP) group analyzed a series of 

typical human body motions and postures useful for defining virtual human motion via avatar 

Public Cloud Based Storage

Storage $11,893/yr

Admin $7,000/yr

Total $18,893/yr $1,574/month

MSFC Hosted Approach

Storage $13,621/yr

Admin $7,000/yr

Total $20,621/yr $1,719/month

Local Server in EV74

Storage $500 (one time hardware upgrade)

Admin $8,000/yr 80 hrs at est. $100/hr

Total $8,000/yr + $500 (one time) $667/month
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technology. These were generic and not tied to specific ground processing tasks. It was 

determined, through further research defining ground processing-typical motion elements, a 

library could be assembled which would permit virtual modeling of typical ground crew 

operations, including technicians, engineers, quality inspectors, and safety personnel. By 

utilizing the MSFC VEL, it was determined the NESC could provide a reliable and realistic 

family of motions and postures. These data, when linked by a designer, could define in detail a 

conceptual or advanced fidelity worker-vehicle process, permitting myriad of ground assembly, 

maintenance, inspection, test and checkout, and troubleshooting operations. 

Work completed by the HEMAP group was assessed and augmented for this effort. Hence, 

serving as the initial baseline; previous studies provided beginning groundwork for virtual 

simulations using avatars to assess and depict pre-launch operations. The KSC study 

emphasized defining elements and the current MSFC effort subsequently provided elements that 

can be chained to create ground operation sequences for stakeholders. Products from the KSC 

studies were utilized as a foundation for the MSFC study for experimental design, task procedure 

definition, and human motion and modeling expertise. Risk and safety concerns from previous 

studies were integrated into this pilot study. Images and perceptual information provided context 

for building relevant motion capture sequences. 

The motions and postures identified in the KSC HEMAP study as essential in this study 

included: 

1. Leaning 

2. Reaching to various angles 

3. Lifting up to 44 pounds to various heights 

4. Squatting 

5. Squatting while holding weighted object 

6. Bending to various angles 

7. Bending while holding weighted object 

8. Kneeling 

9. Kneeling while holding weighted object 

10. Lying down on stomach, side, and back 

11. Installing/removing object in combination with identified motions and postures 

12. Walking 

13. Walking while holding weighted object 

14. Stepping up, down, and/or over 

15. Climbing 

The tasks simulated for motion capture represented as many of these as reasonably possible. 
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7.5 Mockup Development 

The VEL transitioned from primarily plywood and PVC mockups in Phase 1 to customizable 

wireframe mockups in Phase 2. In 6 to 8 weeks, the design and fabrication team developed a 

cutting station for steel rod structural elements; modeled, procured, and fabricated two types of 

multi-insertion connectors and constructed several customizable iterations of launch vehicle 

worksite mockups. 

Simulated surfaces were achieved with plastic, large-mesh netting attached to wireframe mockup 

structures. This provided benefits to VEL efficiencies. First, there were significant 

improvements in documenting participant movements. Near-infrared camera line-of-sight to 

reflective joint markers was not obstructed by plywood mockup surfaces and digital video 

captured motion sequences that occurred outside and inside a simulated volume. Further testing 

is required to determine if the steel rod reflective surfaces caused issues with accurate marker 

tracking. Second, the mesh surfaces provided realistic context of the physical worksite and 

perceived visual obstructions for study participants. Further studies could assess the effect on 

realistic task performance. With sufficient camera coverage, small solid mockups might be used 

for motion capture. However, only minimum success is anticipated for simulated worksites with 

increasing complexity. Some obstruction of reflective anatomical markers must be expected 

from the data collection system. For this simulation to be useful there must be some level of 

low-fidelity physical mockups to provide an interfacing volume and mass and also handheld 

objects providing additional context for critiquing a worksite design concept. Finally, the mesh 

surface treatment is a low-cost, lightweight material that can be rapidly attached, modified, and 

removed, as mockup volumes need to be installed, updated, transported, and stored. 

7.6 Motion Data and CAD Transferability 

The KSC HEMAP team completed an assessment showing that the two human simulation-based 

software best used in conjunction with motion tracking are Jack and DELMIA software [ref. 6]. 

Since VEL operated only Jack software at the time of this study, the focus of this effort was on 

the capability of using motions and postures within Jack environment. 

There are two primary, interrelated ways the MSFC team managed the file formats and motion 

capture software used for the database. First, the decision was made to not use the C3D file 

format because it requires strict naming and organization of support files, or extensive manual 

editing of internal names embedded in the C3D file to function properly in the Jack software. 

The C3D format is considered a standard for the 3-D motion capture industry and is supported by 

major companies that perform biomechanics, animation, and gait analysis [ref. 5]. However, it 

was found to be an inconsistent standard between two different VEL software programs and 

these constraints were not conducive to the adaptability needed for a pilot study. In several file 

tests with Siemens technical support, the VEL team was unable to efficiently transfer compatible 

C3D files from Cortex to Jack software. There were some success in implementing C3D files to 

Jack with extensive manual C3D file editing and the use of the Siemens-supplied environment 

specifically configured for C3D files. Even though DELMIA and Jack may “technically” use 
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C3D format, the difficulty of implementing C3D files in the Jack software did not justify using a 

common file format shared by two (or more) human modeling software programs. 

These C3D constraints relate directly to the second limit on scope. The pilot database is 

populated with motion capture data intended for Jack software. The marker placement on 

participants and the corresponding bones template can be optimized for Jack, DELMIA, or other 

DHM software. Jack software is the DHM application used by the MSFC team and the KSC 

HEMAP group, so optimizing for the Jack software was seen as the lowest impact to 

demonstrate the PMD concept in the available timeframe. However, some stakeholders use 

DELMIA or Pro/ENGINEER®

 software and would need to collaborate with Jack software users, 

or purchase the software to utilize the PMD. In the future, improvements to the C3D format, 

translation or bone calculation methods, or marker placement templates could allow the VELdirected database to support Agency DHM users. Within MSFC, there is an internal database of 

raw recorded motions that were edited and translated into Jack motion and posture files. For 

future continuation of this database task, the internal database would need to be assessed for the 

ability to reuse the raw files to produce motion and posture files optimized for DELMIA and/or 

Pro/ENGINEER®

. 

7.7 Motion Data - Processing and Playback 

Motions were recorded through Jack software with a motion capture module that connects to the 

Cortex software (Figure 7.7-1). An avatar can be assigned to the skeleton created in the Cortex 

software. When a recorded motion with a calculated skeleton is played in the Cortex software, 

the Jack avatar moves simultaneously. The avatar motion can be recorded through the Jack 

software as a “channelset” file. The Jack software add-on module has an animation window 

where users can load channelsets and assign an avatar. Users can clip a channelset to make new, 

shorter channelsets that contain only the desired motions. The ease of creating, editing, and 

loading channelsets makes this approach preferable over using the C3D format. 
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Figure 7.7-1. Example of Creating a Motion Sequence by Combining Channelsets 

7.8 Motion Data - Calibration and Capture 

All motion capture recordings start with the calibration of the 16-camera system to ensure the 

highest degree of accuracy and minimizing the number of incorrectly identified markers 

(i.e., ghost markers). Participants change into a suit and markers are placed on the suit based on 

the pre-determined locations. In the current marker-set, there were 53 markers that must be 

carefully placed on the participant’s body to ensure they were aligned with the anatomical 

location to increase the accuracy of the avatar’s fit to the participant’s body. Figure 7.8-1 shows 

the marker locations. 
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Figure 7.8-1. Study Participant Wearing Motion Capture Suit with Reflective Markers 

For every new participant, several actions must be accomplished to complete a successful motion 

capture session. First, the participant is recorded doing a still T-Pose. This recording allows the 

Cortex software to calculate the skeleton bones and adjust the avatar size. The skeleton bones 

must be calculated because the Jack software utilizes only the skeleton bone motion and not the 

suit markers. Every recording starts and ends with a T-Pose, which is required for proper marker 

identification and gives the VEL team defined start and stop points for each recording. 

The second type of recording is ROM, which are necessary for template creation. The 

participant performs simple ROM to “teach” the software their unique motion capabilities/ 

ranges. ROM include wrists rotation, ankles rotation, hip rotation, leg rotation, head rotation, 

squat, twist, bending over, walking around, and jumping jacks. In Phase 1, each new participant 

would perform a ROM capture and have a template created from that capture. Phase 2 utilized a 

single template for all participants created from a single detailed ROM capture. This was 

possible by using a tool within the Cortex software called “New Subject” which takes a 

T-Pose capture and resizes the default template to fit that specific participant. This allowed the 
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VEL team to save time in the “start-up” phase for each participant and required less time before 

each session to get motion capture sessions setup. ROM recordings are not required to produce 

data, but were necessary for template creation. Through the use of templates, the motion capture 

software was able to better identify markers and generate improved skeleton structures. This 

resulted in a lower post-process time for the VEL team and allowed focus on other aspects of the 

motion capture sessions. 

The third type of recording was task demonstration. Unlike the recordings of T-Pose and ROM, 

PMD task recordings were live recorded by digital cameras. Repeat recordings can be made of 

the same task/subtask if deemed necessary by the VEL team (e.g., bad motion capture data or 

task uncertainty by the participant). All live and motion capture recordings are retained for data 

and record keeping purposes. Because a motion capture session can include any mix of 

tasks/subtasks, file naming of motion capture recordings are at the VEL operator’s discretion. 

The session logs and database documentation contain the recording date, order of recordings (for 

comparison with live motion recordings), Cortex motion file names, and a detailed motion 

description for all recordings. 

7.9 Motion Data – Post-Processing 

VEL operators clean up marker data for useable motion capture recordings to ensure the captured 

motion data is as close to the participant motions as possible. PMD task data is often messy 

because of mockup interfering with marker tracking, or because specific motions or postures 

covering up certain markers at points during the capture. Post-process cleanup allows VEL 

operators to manually smooth marker shaking and to fill gaps in marker data. Marker data clean 

up can take a significant amount of time, requiring a day or two for each motion capture 

recording session. Each participant has multiple usable motion capture recording sessions, 

translating to a baseline estimate of between 1 to 2 weeks to clean up data per participant. 

After the data clean up, skeleton bones are calculated. Theoretically, the bones should adjust to 

the participant size. However, calculating bones for larger girth/hip participants proved 

problematic because markers representing the anterior superior iliac spine anatomical landmarks 

were significantly offset from the actual landmark. When the hipbones are calculated, the 

software assumes the bones should be closer to the front of the person, thus causing the spine to 

artificially angle. Figure 7.9-1 shows a comparison between participants with average and large 

girths. At project completion, the team was consulting with Motion Analysis Corporation, the 

company that produces the cameras and Cortex software, to resolve this issue. Other issues 

found during the skeleton calculation process can usually be found in the hand and head areas. 

The skeleton calculation software sometimes has difficulty determining the length of certain 

body segments, which can result in a deformed skeleton structure. The end result of these 

skeleton deformations can occasionally cause the Jack software to animate the avatar in a jerky 

manner, cause the arms and hands to be angled, and makes the back or head pop in an unusual 

fashion. At this point, the skeleton definitions used were those provided to the VEL by the 

Motion Analysis Corporation. To edit these definitions to solve problems or generate proprietary 
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skeleton definitions, an additional software module, SIMM, would need to be purchased. After 

calculation of the bones, VEL operators produce Jack channelsets of the raw recordings from the 

Cortex software. A channelset is a type of motion recording that can be played in the Jack 

software. The raw recordings capture the entire motion capture sessions and can be separated 

into subtask channelsets, element postures, and element channelsets. 

 

Figure 7.9-1. Participant 001 with an Average Girth and Participant 006 with a Larger Girth 

While VEL operators perform the activities detailed in the abovementioned paragraph, human 

factors engineers review the live motion videos and develop a task breakdown worksheet. This 

worksheet lists motion capture sessions, corresponding Cortex file names, details the motion 

descriptions, approximate time stamps for the start/end of each subtasks, and each key posture 

for a given participant (Table 7.9-1). The task breakdown worksheet contains the PMD search 

keywords and Jack file names associated with each element. See Appendix E for motion 

segmentation using the task breakdown worksheet. 
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Table 7.9-1. Example Task Breakdown Worksheet with Segment Times and Descriptions 

The live videos are edited to extract videos, one for each subtask, and named according to PMD 

file name structure. Upon receiving the task breakdown worksheet, VEL operators review each 

raw channelset, refine the time stamps in the task breakdown worksheet, produce the posture 

files and screenshot picture files for each key posture, and edit channelsets that represent 

subtasks and/or elements named according to the PMD file structure. All subtask channelsets are 

screen recorded to produce videos. Analyses, which include lower back, static strength 

prediction, and fatigue analysis, are performed for each subtask channelset. A Jack environment 

that contains the human figure with the matched anthropometric data, stationary objects that 

represent mockups (if available), and postures are archived. Tests are performed for each 

environment folder to ensure the working operation of associated channelsets and postures. This 

is important since an environment file within the Environment folder has file linkages to access 

the other files within the same folder. All environment, analysis, media, and channelset files are 

named and reorganized to a strict file structure to be zipped into a packet. 

Each compressed file contains a single task and the associated subtasks/elements. Files adhere to 

a naming structure showing at which level (i.e., task, subtask, and element) the information is 

provided. Files are organized in four folders according to the type of file (i.e., Channelset, Data, 

Media, and Environment). All of the examples shown would be found in the compressed folder 

“sub-001-hatch-01.zip.” The reason for files to be compressed at the task level is three-fold. 

One reason is only one Jack environment needs to be provided for each of the associated subtask 

motions and element motions/postures. Another is the environment file depends on folder links 

for a Jack environment to operate. Therefore, it is important the Environment folder as a whole 
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is downloaded and intact. Lastly, a user may want the motions associated with that task and it is 

easier to perform one download of the whole task rather than searching for the associated 

subtasks/elements and performing multiple downloads. 

When opening the folder, there will be four folders for each subtask. If the user wants to see 

images, then the files will be located in the Media folder. If the user wants to see analysis, then 

the files will be located in the Data folder. If the user wants to create a simulation out of 

channelset motions, then the environment file is opened from the Environment folder and 

channelsets can be added from the Channelset folder. Posture files have been incorporated into 

the environment, so the user does not need to upload posture files into an environment. Upon 

opening the Jack environment for a given task, the figure has the associated posture attached. 

Table 7.9-2 shows the User’s Guide detailing how to use the database and the channelsets and 

postures within Jack software (see Appendix G for additional details). 

Table 7.9-2. User’s Guide for Database 

7.10 Motion Data – Observations, Issues, and Improvements 

Participant 001 was used for prototype database generation with a solid surface plywood hatch 

mockup. This mockup significantly interfered with camera tracking of the markers, especially 

on the hands. When Participant 001 performed the edge cover installation, the 4 markers in each 

hand disappeared. The Cortex software can often guess the location of a missing marker based 

on the locations of nearby markers. However, if several linked markers are missing (e.g., four 

hand markers), the software cannot approximate the hand bone location. This issue was resolved 
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by creating a wireframe hatch, which significantly improved the motion capture data. 

Interference from the wooden hatch was apparent with markers in close proximity to the 

reflective wooden surface producing ghost markers. This phenomenon could be mitigated with 

matte painted surfaces. 

In Phase 1, recordings were required to be completed within the same session. Suit changes can 

shift the marker position and alter the bone calculations. Markers are often utilized on different 

suits due to their limited quantity. It was difficult to replace markers in exactly the same place as

before. Part of the procedure and expectation for the participants was they commit to one long 

session to complete all recordings. Participants could return for additional recording, but they 

would have to be treated as a new participant in terms of motion capture data. 

For Phase 2 this issue was minimized. Through use of the default template created for Phase 2 

and “New Subject” tool within the Cortex software, issues surrounding marker shifting and/or 

swapping participants were rectified. This process helped alleviate the issue surrounding 

markers being removed from one suit to be placed on another because of the limited number of 

markers available. Additional markers were purchased for Phase 2 to address this issue. 

However, the total number of markers available is still less than the number that would be 

required to outfit each participant suit individually. These improvements allowed Phase 2 to 

have more freedom in session scheduling and it was left to each participant to decide between a 

single long session and several shorter sessions. 

All recordings started and ended with a T-Pose. This allowed the Cortex software to identify the 

participant and markers. The software tracked markers based on the continuity of time and 

space. If the software lost track of too many markers during the recording, then a T-Pose posture 

at the end of the recording could be used as a starting point and track the markers backwards in 

time. 

During the breakdown of motion capture sessions, it was observed that some participants rushed 

from one subtask to another. This caused awkward subtask start and end positions. For 

example, a motion capture session would involve installing protective covers then installing a 

LRU. Installing protective covers and installing LRU are two separate independent subtasks. A 

participant would finish installing the protective covers and retrieve the LRU with hands 

extended. This did not produce a defined stopping/starting point during this transition between 

subtasks. Briefing the participants was subsequently revised to include the advisement to not 

rush and include “pauses” between motions. 

Lower back, fatigue, and static strength prediction analyses were the only three time-based 

analyses offered by the Jack software. An add-on software module called the Task Analysis 

Toolkit (TAT) Reporter allowed analysis outputs to comma-separated values (CSV) Microsoft®

Excel spreadsheets with analysis values at each time interval. Jack software offers other analysis 

types, including: rapid upper limb assessment, NIOSH, Ovako working posture analysis, and 

manual handling limits. Any of these analyses can be performed by the Jack user on channelset 

motions, a series of channelset motions, or individual postures. Initially, the results of NOISH 
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analysis was planned to be an output of the database package. However, the methodology of 

calculating the NIOSH values requires two postures (i.e., from point A to point B) and other data 

(e.g., object weight). Each user would have different inputs for the NIOSH analysis, so even 

though the analysis can be part of the data package, it is more effective to defer to the user to 

perform the analysis. More details on the NIOSH lifting equation can be found in Appendix J. 

When chaining element motion channelsets to create a new subtask motion channelset, there was 

the possibility of gaps between start and stop points that cause the avatar to “jump.” This effect 

resulted from instantaneously changing posture and/or location. There are techniques for 

smoothing those transitions that are addressed in the PMD tutorial. 

Finally in Phase 1, only the human body motions were captured. There were two other types of 

entities that could potentially be captured for playback: objects and hands/fingers. Markers can 

be placed on objects and the Cortex software can simultaneously recognize multiple entities 

(e.g., humans and objects). A singular “bone” is used in the Cortex software to represent the 

object and attached to a CAD model in the Jack software. So, when the physical object moved, 

so did the CAD model in the Jack environment. There has been success in performing a live 

demonstration of a tracked human manipulating a tracked object in a Jack environment. 

However, recording the motions of a human and an object simultaneously as a Jack channelset 

has yet to be assessed in the VEL. 

Phase 2 began the process of integrating object tracking with the human tracking being 

performed. While not all objects were tracked, several were in an attempt to generate a better 

data set for the software user. Examples of objects tracked in Phase 2 include a wireframe LRU, 

a wooden battery LRU, and a plywood hatch door. Phase 2 did not incorporate hand tracking 

into the final data set because of time limitations. 

7.11 Motion Data – Fingers and Hands 

The other entities yet to be tracked are fingers. In this study, the fingers were fixed on the 

avatars. Previous VEL experience has shown using markers on each finger segment 

demonstrated poor results because of too many markers in close proximity. An increased 

number of cameras or upgraded cameras with a higher resolution might allow this type of hand 

tracking. Cybergloves were obtained prior to study initiation and used to track the movement of 

each finger segment by flexion and abduction sensors. Cybergloves were not initially used for 

this study because the primary focus was on the human body motions. However, being able to 

grip and reach is a desired motion to capture by some human factor engineers. Motion capture in 

conjunction with a singular cyberglove was successfully implemented for a live demonstration in 

the Jack software. There were several obstacles to being able to record both cybergloves 

simultaneously with human body motion capture. First, data from the cybergloves were 

transmitted via Bluetooth. Transmitting two data streams at the same time wirelessly can be 

problematic. The second obstacle was the current VEL procedure did not easily allow for 

cyberglove data recording. Data from cyberglove streams directly to the Jack software, which is 
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independent from the Cortex software data stream. The schematic shown in Figure 7.11-1 

depicts the two different data streams into Jack software. 

Figure 7.11-1. Simple VEL Schematic 

There were two possible solutions to these issues. The first solution is to record a participant 

doing a T-Pose and several ROM captures to create a template and calculate the participant 

bones, or use the default template created from a detailed ROM capture and use the “New 

Subject” tool within the Cortex software to apply the template to the participant in question. 

While doing a PMD task, Cortex software and cybergloves would have to be fed live data stream 

to the Jack software, which is the procedure for live tracking motions. With the two live data 

streams, the software can record data streams simultaneously as a channelset. The challenge 

with this solution is the motion data is likely to be inaccurate without the post-process data clean 

up. With improvements in template creation and by filling marker gaps virtually, this process 

may become feasible. Given the time to research this, it may be possible to record channelsets 

directly from the software and skip the post-process clean up in certain cases if various 

improvements can be made. 

The second solution is while performing a PMD task, record the human body motions through 

the Cortex software and record the cyberglove motions through the Jack software as a 

channelset. After cleaning up the human body motion data, the Jack software records the 

motions of the cleaned up data as a channelset. There may be a way to simultaneously combine 

two channelsets as one motion. It is uncertain if this solution is feasible. An assessment must be 

made to determine if incorporating cyberglove data is feasible and whether it is beneficial 

enough to justify the additional effort. 
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7.12 Motion Data – Aligning Positions 

All motion data (channelsets) have an associated coordinate system that allows the environment 

to be manipulated to change the scenery around the motion. However, if two motions were 

linked and occurred in different areas based on the same coordinate system, there would be a 

jump in terms of positions. For example, if there are two copies of a channelset motion of a 

person walking from point A to B and they are played back-to-back, the entire motion would 

show a person walking from point A to B, instantaneously jump back to A and walk from point 

A to B. Some users may want to be able to retrofit the start point of a motion to the end point of 

the previous motion. It is unlikely to be able to reset the coordinate system in the middle of the 

motion so that the person would be able to walk from point A to B to C. This limitation must be 

kept in mind when creating a string of channelsets. 

7.13 Task Performance 

In general, participants had minimal trouble completing the prescribed subtasks and some were 

surprised the capture sessions did not last longer or involve more complex ground processing 

tasks. However, the shorter female participants experienced difficulty with completing subtasks 

that required far reaches up and inside the hatch, reaching certain connectors in the connector 

mockup, and with reaching over to transfer the battery LRU past the simulated gap at the 

platform edge and through the hatch onto an internal shelf. Taller male participants were forced 

to duck their heads during hatch ingress/egress and bend over farther for lifting/lowering tasks. 

These are desirable behavioral results and participant impressions for several reasons: 1) clean 

quality data were captured with minimal failures or fatigue; 2) extensive task rehearsal was not 

necessary; 3) participants rarely turned their heads or took long, unnatural pauses to ask 

questions; and 4) participants left with a positive impression of the experience. Figure 7.13-1 

shows the participant postures for each subtask. The subtask sequences used during motion 

capture sessions are detailed in Appendix C.
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Figure 7.13-1. Participant Postures while Performing Subtasks in Phase 1 
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7.14 Human Factors Analysis 

Three types of analysis data were provided in CSV format as part of each compressed file: static 

strength prediction, fatigue analysis, and lower back analysis. These analyses were conducted in 

Jack software on channelsets at the subtask level. Figure 7.14-1 shows three different postures 

extracted from a Jack subtask animation and the corresponding frames from live video. 

Figures 7.14-2 and 7.14-3 show the possible analysis results from the raw data provided, or from 

custom outputs from the Jack software using channelsets and the Analysis window or the TAT 

Reporter module. Please refer to the “VEL Instructions”2 or the Jack software manual for how to 

utilize the analysis capabilities. 

 

 

Figure 7.14-1. Three Postures during LRU Transfer Subtask, Live Video, and Jack Software 

Animation 

 

 

2

VEL-Motion-Capture_Instructions.docx
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Figure 7.14-2. Example Output from Jack Software for Low Back Analysis 

Figure 7.14-3. Example Output from Jack Software for Static Strength Prediction 
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7.15 NIOSH Lifting Limits 

In 1981, in response to OSHA law, NIOSH created a lifting limit equation to reduce poor lifting 

practices injuries. Research indicated a third of compensated industrial injuries were back 

injuries. Industry is required to apply the equation per the OSHA General Duty Clause, which 

demands an environment “free from recognized hazards that are causing or are likely to cause 

serious physical harm.” A revised equation must be applied to where lifting applications may 

cause employee harm and serves as an ergonomically measurable analysis tool. The equation 

addresses two aspects of lifting and carrying. They are the action limit (AL) and the maximum 

permissible limit (MPL), with the latter being achieved only by trained personnel. The equation 

is explained in detail in Appendix J. It is a function of the Jack software and will predict upper 

limits in mass handling in a virtual ground processing environment. It also was addressed for the 

human subjects performing the test activities necessary to obtain the library element data. 

7.16 Database Implementation 

The database was designed to support human factors stakeholders throughout the NASA 

community by developing a dynamic webpage with the PMD stored in a MySQL database linked 

to the webpage (see Figure 7.16-1). Because of limited schedule and budget for the pilot phase, 

the PMD resides on an internal server. To facilitate the development, MAMP was loaded on a 

Macintosh workstation. MAMP is an open source package that provides a local PHP 

development environment. When development is complete, the database and webpage scripts 

were moved to the MSFC server for implementation. The MAMP system provides PHP and 

MySQL administrative tools, which provide the ability to create the database and its tables, to 

define indexes in tables, and links between tables. They provide a means to load and retrieve 

data and perform queries. PHP scripts that address the database can be developed and tested 

locally and over the MSFC network. 
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Figure 7.16-1. Pilot Phase PMD Topology 

7.17 Website Interface 

The database team established search and download techniques that would make the various 

types of data easily understood and retrievable by the user. Emphasis was placed on supporting 

the users with an intuitive, functional database. Figure 7.17-1 shows web interface for the pilot 

database. Searches are made using element, subtask and task keywords, and human operator 

(participant) characteristics. Results are displayed as a list of elements, with thumbnail images, 

operational relationships (i.e., corresponding Function and Task), and a link to downloadable 

task-level data packet. Methods for hosting and accessing data were researched. See 

Appendix G for additional technical details on database structure. 
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Figure 7.17-1. Example Webpages for PMD Search, Display, and Results Pages 

8.0 Findings, Observations, and NESC Recommendations 

Findings in this study address salient points that should be considered in future efforts for 

additional study pursuit. 

8.1 Findings 

The following findings were identified: 

F-1. Based upon the prototypical study results, a motion capture database is feasible and can 

be used in the aerospace industry with appropriately trained operators, analysts, and 

available software. 

F-2. With the Jack software, users are able to link motion elements (segments) to create 

subtasks within CAD environments containing workspaces and objects. 

F-3. The defined motion capture elements created in the database can be feasibly linked to 

produce other performance simulations of varying length. 
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F-4. The NIOSH lifting equation cannot be accurately calculated by using only the Jack 

software as it only measures at two points (start and end) and does not include the various 

body measurements one might experience between the two points. 

F-5. The Jack software was constrained to simple motions and postures which, when chained 

into subtask operations, periodically had missing data (gaps) depicted as no avatar figure 

in a chain of motions or the avatar instantaneously relocating or changing posture. 

F-6. Use of cybergloves and/or finger markers would allow analysts to capture and analyze 

the dexterity of a participant while performing tasks and would increase the fidelity of 

motions stored in the PMD. Use of participant head-mounted display would impact 

mockup fidelity, with augmented reality only requiring physical “touch points” versus 

entire visible mockup. 

F-7. The pilot study simulations displayed fixed hand positions when interfacing with virtual 

equipment where details of hand gripping, pinching, and reach positions were not 

available. 

F-8. The pilot study used software and a database system on a limited access server within the 

MSFC firewall. Existing software/database access protocol must be addressed at MSFC 

and Agency levels to enable database access. 

8.2 Observations 

The following observations were identified in the study: 

O-1. The number of test participants used was minimally sufficient to gather prototypical pilot 

data and prove the concept. 

O-2. To drive the motion capture, typical representative subtasks were utilized from as many 

postures and motions from the identified list (see Section 7.0) as feasible and could be 

applicable to any spaceflight vehicle. 

O-3. With sufficient camera coverage, small, with respect to the participant, solid mockups 

might be used for motion capture. 

O-4. As the 5th and 95th percentile persons only exist as an ideal for assessing body 

measurements, stature and reach were appropriate measures to emphasize when 

recruiting from the available test participant pool. 

O-5. In Phase 1, only the human body motions were captured. 
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8.3 NESC Recommendations 

The following recommendations were identified and directed towards the Office of Primary 

Responsibility for the NASA SFHSS, NASA-STD-3001 Volume 2, and the Human Integration 

Design Handbook (HIDH). 

R-1. Expand the PMD to meet the needs of projects and programs like GSDO and SLS in their 

launch vehicle ground processing and maintenance design trades and analyses. 

(F-1 though F-8, O-1, O-2, O-3, and O-5)

R-2. For the purposes of verification, expand the definition of modeling to include digital 

human models simulating a range of anthropometric measures, such as 95th percentile or 

more male and 5th percentile or less female. (O-4)

9.0 Alternate Viewpoint 

There were no alternate viewpoints identified during the course of this assessment by the NESC 

team or the NRB quorum. 

10.0 Deliverables 

PMD 

The study deliverables include a prototype PMD library of posture and motion elements 

representative of what might be provided in detail with additional resources. The pilot study 

database library had adequate connectivity within its components and with representative data 

input to allow the concept to be demonstrated and verified. However, a more comprehensive 

version will be required to meet the needs of pre-launch spaceflight vehicle processing design 

and operations. 

User’s Manual 

A user’s manual accompanies the database so that subsequent users can understand the protocol 

and logic for the program and how the data may be utilized in digital human modeling software 

for design and analysis. 

11.0 Lessons Learned 

LL-1. There is great potential in using motion capture technology to capture real human 

postures and motions for incorporation into digital human modeling environments, but 

there are limitations. Engineering needs this knowledge and it can be captured in useful 

ways; however, there is still significant work to be done to validate the models as 

appropriate for requirements verification. 
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12.0 Recommendations for NASA Standards and Specifications 

The recommendations for NASA standards and specifications include the following: 

• Add to NASA SFHSS NASA-STD-3001 a recommendation on how to successfully 

engineer for ground support operations and maintenance by using the techniques used to 

create this database and the postures and motions contained in the database. 

• Modify NASA SFHSS NASA-STD-3001 to allow requirements validation with digital 

human models that exhibit anthropometric measures that are within a range meeting the 

intent for corresponding applicable 5th or 95th percentile body dimensions. 

• Add a section to the HIDH explaining the cost-benefit analysis of using digital human 

modeling in 3-D CAD environments to simulate human interactions in 1-G worksite 

design, with the caveat being the known limitations (such as the inability to capture hand 

dexterity and lifting mass) of virtual simulation. 

13.0 Definition of Terms 

Channelset 3-D human motion file (.env format) of specific time duration, recorded in 

Jack software and applied to avatars for motion simulation. 

Corrective Actions Changes to design processes, work instructions, workmanship practices, 

training, inspections, tests, procedures, specifications, drawings, tools, 

equipment, facilities, resources, or material that result in preventing, 

minimizing, or limiting the potential for recurrence of a problem. 

Finding A relevant factual conclusion and/or issue that is within the assessment 

scope and that the team has rigorously based on data from their 

independent analyses, tests, inspections, and/or reviews of technical 

documentation. 

Lessons Learned Knowledge, understanding, or conclusive insight gained by experience 

that may benefit other current or future NASA programs and projects. 

The experience may be positive, as in a successful test or mission, or 

negative, as in a mishap or failure. 

NIOSH Lifting A method for quantitatively assessing the physical stress of two-handed 

Equation manual lifting tasks. 

Observation A noteworthy fact, issue, and/or risk, which may not be directly within the 

assessment scope, but could generate a separate issue or concern if not 

addressed. Alternatively, an observation can be a positive 

acknowledgement of a Center/Program/Project/Organization’s operational 

structure, tools, and/or support provided. 
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Problem The statement of a subject meriting research with an independent technical 

assessment. 

Proximate Cause The event(s) that occurred, including any condition(s) that existed 

immediately before the undesired outcome, directly resulted in its 

occurrence and, if eliminated or modified, would have prevented the 

undesired outcome. 

Recommendation A proposed measurable stakeholder action directly supported by specific 

Finding(s) and/or Observation(s) that will correct or mitigate an identified 

issue or risk. 

Root Cause One of multiple factors (events, conditions, or organizational factors) that 

contributed to or created the proximate cause and subsequent undesired 

outcome and, if eliminated or modified, would have prevented the 

undesired outcome. Typically, multiple root causes contribute to an 

undesired outcome. 

Supporting Narrative A paragraph, or section, in an NESC final report that provides the detailed 

explanation of a succinctly worded finding or observation. For example, 

the logical deduction that led to a finding or observation; descriptions of 

assumptions, exceptions, clarifications, and boundary conditions. Avoid 

squeezing this information into a finding or observation. 

14.0 Acronyms List 

3-D Three-dimensional 

AL Action Limit 

ANSUR Army Anthropometric Survey 

ARC Ames Research Center 

CAD Computer-Aided Design 

CSV Comma-separated Values 

DHM Digital Human Modeling 

EPA Environmental Protection Agency 

G Gravity 

GSDO Ground Systems Development and Operations 

GSE Ground Support Equipment 

GUI Graphical User Interface 

HEMAP Human Engineering Modeling and Performance 

HFE Human Factors Engineering 

HIDH Human-Integration Design Handbook 

IH Institutional Health 

IRB Institutional Review Board 

IT Information Technology 
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JSC Johnson Space Center 

KSC Kennedy Space Center 

L/C Likelihood/Consequences 

LR Level of Risk 

LRU Line Replaceable Unit 

MAMP Macintosh -Apache - MySQL – PHP {development package} 

MPCV Multi-Purpose Crew Vehicle 

MPL Maximum Permissible Limit 

MSFC Marshall Space Flight Center 

NESC NASA Engineering and Safety Center 

NIOSH National Institute for Occupational Safety and Health 

NRB NESC Review Board 

NSC NASA Safety Center 

OSHA Occupational Safety and Health Agency 

PMD Postures and Motions Database 

PVC Polyvinyl Chloride 

ROM Range of Motion 

SCAPE Self Contained Atmospheric Pressurized Ensemble 

SFHSS Space Flight Human System Standard 

SIMM Software for Interactive Musculoskeletal Modeling 

SLS Space Launch System 

SME Subject Matter Expert 

SRB Solid Rocket Booster 

TAT Task Analysis Toolkit 

TBD To Be Determined 

VAB Vertical Assembly Building 

VEL Virtual Environments Laboratory 

VPN Virtual Private Network 

15.0 References 

1. NRD Request # TI-12-0774; Computer-Aided Design (CAD) Tools to Support Human 

Factors Design Teams: Primitive Models Database. 

2. 1-G Human Factors for Optimal Processing and Operability of Constellation Ground 

Systems; Section 5; Stambolian, Damon B.; NASA KSC.

3. NASA MSFC Human Research Category II Protocol; Computer-Aided Design Tools to 

Support Human Factors Design Teams: Primitive Models Database; September 25, 2012. 

4. Postures & Motions Library, 11-16-2012 Project Status, Jacobs ESSSA Group, ESSSAFY13-232_Motions-Database-DRAFT-b.pptx. 
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5. C3D.org Cramp, Edmund. The 3D Biomechanics Data Standard. 16 January 2013. 

23 January 2013 <http://www.c3d.org/ >. 

6. NIOSH Equation; claymore.engineer.gvsu.edu/~buters/egr470/analysistool.html; Grand 

Valley State University. 

7. Human Factors/Worksite Analysis Tools for Immersive/Motion Capture Labs, 

December 2011, NASA KSC, MSFC BPA NNM09AA00Z, Task NNM11AA76THEMAP. 

8. 1988 Anthropometric Survey of U.S. Army Personnel: Methods and Summary Statistics. 

Gordon, Claire C.; Churchill, Thomas; Clauser, Charles E., Bradtmiller, Bruce; 

McConville, John T., Tebbetts, Ilse; and Walker, Robert A., September, 1989, U.S. Army 

Natick Research, Development and Engineering Center. 

16.0 Appendices 

Appendix A. Operational Definitions 

Appendix B. Mockup Configurations and Subtask Examples 

Appendix C. Research Session Tools and Forms 

Appendix D. Motion Capture – User Guide and Lab Processes 

Appendix E. Data Organization and Naming 

Appendix F. NASA Program Risk Scorecard and Ratings Table 

Appendix G. Database Design Structure and Software 

Appendix H. Database Website Interface – July 31, 2013 version 

Appendix I. Human Research Protocol and Consent Form 

Appendix J. National Institute for Occupational Safety and Health (NIOSH) Lifting Equation 

(OSHA) 

Appendix K. Phase 2 Quick Look Test Reports 
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Appendix A. Operational Definitions 

A-1. Operational Definitions - Timeline View 

 
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A-2. Operational Definitions – Function-to-Element Flow-down
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Appendix B. Mockup Configurations and Subtask Examples 

 

B-1. Solid Surface Hatch Mockup, GSE Shelf with Door and Battery LRU 

 

 

B-2. PVC “Wireframe” Hatch Mockup with Simulated Protrusions/Covers, Battery LRU on Floor 
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B-3. Phase 1 Mockup Details: GSE Shelf, Adjustable toe-kick, Handles on Clear Door 

B-4. Phase 2 Mockup Details: Toe-kick/Simulated Platform Edge with Steel Rod and Connectors 
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B-5. Phase 2 Mockup of Launch Vehicle Stage Adapter Wall Section with Hatch Opening, Connectors 

Requiring Tool Manipulation (right side) and Simulated LRU Equipment Shelf Attached to Plywood 

Structure 

 

B-6. Phase 2 Mockup Details: Door on GSE Shelf, Overhead LRU, and Overhead Connection 
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Appendix C. Research Session Tools and Forms 

NESC Participant Sessions - VEL Document Checklist 

The following scripts, forms, and data collection tools should be printed and/or available for 

viewing prior to each task simulation and motion capture session. 

1. Research Activity Description: Provides overview to acquaint session leader with the process 

and provide a reference script for talking with participants. 

 

2. Participant Consent Forms (before session begins): Be sure they sign all three pages and 

include their address and media release signatures on third page. Adding post-it flags 

beforehand makes this easier. 

Summarize the form for participants, have them sign two copies--one is for them to keep, the 

other is delivered to the NASA project lead. 

 

3. Data Collection: Demographics and Work Experience (before session begins): Captures level 

of ground operations knowledge and discusses physical limitations again. This form and consent 

forms can be completed before participants change into motion capture suits during orientation. 
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NOTE: This is also a good time to introduce participants to the task simulations with a walkthrough of the VEL mockups and capture environment.

4. Anthropometrics (before session begins): This data can be captured in a separate session prior 

to the task simulation session. It is best to measure participants in motion capture suits or 

athletic clothing they may have brought to wear underneath the suit. Be sure to have the 

anthropometric reference document on hand, with helpful visual instructions for how to measure. 

A clipboard is also helpful. 

 

 
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5. VEL Lifting Tips and Task Demonstration (before session) – 

 

6. Data Collection: Participant Feedback (during session) - Used during task demonstration/lifting 

training and before starting the first capture.

 

Before Participant Leaves: Check that necessary data has been collected (e.g., signatures, 

written data, motion capture tasks and calibrations, video, participant personal photos in suit [if 

desired]) and thank them again for their time!

 

After the Session: Check in with team on session successes and improvements, high five each 

other, take a break, then transcribe written notes, and write session debrief—ideally, before the 

next session begins. 

Enter data into corresponding spreadsheet files, deliver to database manager, and archive written 

versions in a secure project folder.

 
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__ transcribe researcher notes 

__ write debrief report, email to team and customer 

__ enter data in spreadsheet files 

__ deliver anthropometric data to VEL team ASAP 

__ deliver data to database manager 

__ archive written documentation 

REFERENCE FILES (pdf and editable versions): 

1. Research Activity Description

NESC-VEL_Research-Activity_Description_v1.doc 

2. Participant Consent Forms 

NESC-VEL-Study-Participant-Consent.pdf 

NESC-VEL-Study-Participant-Consent.doc 

3. Data Collection: Demographics and Work Experience 

database-fields_demographics-2012-12.pdf 

data-sessions-anthro-feedback-demographics-2013-08.xls 

4. Anthropometrics – Data Collection and Reference 

database-fields_anthropometrics-2012-12.pdf 

data-sessions-anthro-feedback-demographics-2013-08.xls 

AnthroCollection-Reference_MFSC_2012-12-14.pdf 

5. VEL Lifting Tips and Task Demonstration 

NESC-VEL-lifting-tips-task-demo.pdf 

NESC-VEL-lifting-tips-task-demo.doc 

6. Data Collection: Participant Feedback

database-fields_subject-feedback-2013-08.pdf 

data-sessions-anthro-feedback-demographics-2013-08.xls 
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Anthropometric Measurement Form, Virtual Environments Lab 

 

 

Anthropometric Measurement Data - Virtual Environments Lab (VEL), MSFC

Collected by: MSFC-VEL-Subject #:

Collection date: Stature % (5, 50 or 95):

Collection notes: Gender (M or F):

other subject info:

>>measurements take without shoes; eight bolded items used in JACK software Measurements (cm) *

Vertical 1 Stature x

2 Arm Length (resting at side, acromion to tip) x

3 Acromial Height (shoulder to floor)

4 Waist Height (Navel) x

5 Overhead Fingertip Reach (set tool on box for height) x

Breadth 6 Biacromial Breadth (shoulder points)

7 Bideltoid Breadth (shoulder outside) x

8 Hip Breadth (max pt, feet & knees together) x

Head 9 Head Breadth (max above ears)

10 Head Height (chin to top) x

11 Head Length (forehead to back)

12 Interpupil Distance (from above, rest on forehead)

Tape 13 Chest Circumference (fullest part, pt of max respiration)

14 Waist Circumference (Girth)

15 Waist Circumference (Navel) x

Hand 16 Hand Length (wrist to tip)

17 Hand Breadth (at knuckles)

Vertical 18 Sitting Height (from sitting surface)

19 Eye Height (from sitting surface)

20 Sitting Acromial Height (midshoulder)

21 Elbow Rest Height (sitting, 90 deg)

Arms 22 Shoulder-Elbow Length (acromion-radiale, 90 deg)

23 Elbow-Fingertip (Forearm - Hand Length) x

Waist 24 Abdominal Depth

Legs 25 Buttock-Knee Length

26 Thigh Clearance (to sit surface)

27 Sitting Knee Height 

Feet 28 Ankle Height (lateral malleolus)

29 Foot Length

30 Foot Breadth, Horizontal

Wall 31 Functional Grip Reach (wall to first knuckle)

Scale 32 Weight (kg) x

* ten items to be displayed w/ visuals on database page (weight included w/ stature) Standing Sitting
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Motion Capture Subtask Sequences (Phase 1) 

• Step in/out of hatch (for practice), emphasize arm drops and pauses & reversals 

Configuration 1: Plywood part-task mock-up of hatch w/door, internal shelf, exterior GSE 

shelf 

Segment 1: Hatch & LRU Tasks, Standing External to Vehicle

• T-Pose 

• Approach and remove hatch door, set on GSE handling cart, PAUSE 

• Take protrusion covers to door, PAUSE AT DOOR 

• Lean in to install covers on internal protrusions, PAUSE BETWEEN 

• Lift small LRU from cart shelf & bring to hatch 

• Lean over to set LRU through hatch onto internal platform 

• Stand & PAUSE 

• Retrieve LRU and replace on shelf, PAUSE 

• Lean in to remove covers on internal protrusions, PAUSE BETWEEN 

• Return protrusion covers to shelf, PAUSE 

• Remove door from shelf and close out hatch 

• T-Pose 

Configuration 1a: replace plywood door with acrylic version 

• Repeat door removal and installation 

Configuration 2: PVC wireframe hatch, internal shelf, exterior GSE shelf 

Segment 2: Protrusion Covers and Ingress/Egress (no hatch door)

• T-Pose 

• Take protrusion covers to door, PAUSE AT DOOR 

• Lean in to install covers on internal protrusions, PAUSE BETWEEN 

• Lift small LRU from cart shelf & bring to hatch 

• Lean over to set LRU through hatch onto internal platform 

• Stand & PAUSE 

• Retrieve LRU and replace on shelf, PAUSE 
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• Lean in to remove covers on internal protrusions, PAUSE BETWEEN 

• Return protrusion covers to shelf, PAUSE 

• T-Pose 

Configuration 3: Remove internal shelf (wooden box), exterior GSE shelf 

Segment 3: Hatch Ingress/Egress 

• T-Pose 

• Step through hatch simulator, then step back out, PAUSE BETWEEN 

• Repeat 

• T-Pose 

Configuration 4: GSE platform (table) with PVC hatch ring, exterior GSE shelf 

Segment 4: LRU Operations – Standing Transfer 

• Transfer LRU from GSE shelf to GSE platform 

• Pass through LRU via GSE platform, PAUSE 

• Walk around to be the “recipient” 

• Retrieve the LRU from the table, PAUSE 

• Reverse all actions 

Configuration 5: GSE platform (table), LRU holder on floor, LRU on table 

Segment 5: LRU Operations – Diving Board to Floor Transfer

• T-Pose “inside” vehicle, near battery LRU 

• Stand facing LRU, PAUSE, assume lifting position, PAUSE 

• Move LRU from diving board to holder box on floor 

• Raise torso to resting position, PAUSE 

• Stand and PAUSE 

• Turn for T-Pose 
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Motion Capture Subtask Sequences (Phase 2) 

Reference document: VEL-Mockups-Tasks-Aug-2013-a.ppt 
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Phase 2 Motion Capture Sessions - Example Task Checklist - Aug 2013 DRAFT 

[Typical capture pattern: 1/2 1/2 2/2 ]

Segment A: Wireframe door 

T-Pose > Remove (Hatch to Shelf ) > T-pose 

T-Pose > Install (Shelf to Hatch) > T-pose 

T-Pose > Remove & Install > T-pose 

 

Segment B: LRU Transfer - Exterior 

 

T-Pose > Install (Shelf to Box) > T-pose 

T-Pose > Remove (Box to Shelf ) > T-pose 

T-Pose > Remove & Install > T-pose 

Segment C: LRU Transfer - Interior 

 

T-pose > Install (Shelf to Overhead > Hold > Overhead to Floor) > T-pose 

T-pose > Remove (reverse motions) > T-pose 

T-pose > Install & Remove (Shelf to Overhead > Hold > Overhead to Shelf) > T-pose 

- AND / OR - 

T-pose > Install (Shelf to Overhead) > T-pose 

T-pose > Remove (Overhead to Shelf) > T-pose 

T-pose > Remove & Install > T-pose 

Segment D: Interior Tool Connections 

 

T-pose > Remove cover & attach low connection > T-pose 

T-pose > Remove cover & attach middle connection > T-pose 

T-pose > Remove cover & attach overhead connection > T-pose 

Segment E: Weighted door 

T-pose > Remove (Hatch to Shelf ) > T-pose 

T-pose > Install (Shelf to Hatch) > T-pose 

T-pose > Remove & Install > T-pose 
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Segment F: Electrical Cable Connections 

 

T-pose > attach Cable #1 > T-pose 

T-pose > attach Cable #2 > T-pose 

T-pose > attach Cable #3 > T-pose 

Complete series once without step-up box platform and once with the platform 

Filename of this document: Motion-Capture-Session-Checklist.docx 
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pg ___ of ___ Subject Feedback - Virtual Environments Lab (VEL), MSFC

use more pages if needed MSFC-VEL-Subject #:

Collected by:

Collection date:

During motion capture session (after each recording segment)

>> Capture segment # ___ List major Task/Subtasks below:

(max 50 characters)

On a scale of 1 to 5, with 5 being most difficult, how would you rate that task?

(# between 1-5)

Which postures or motions did you find most difficult?

(max 50 characters)

Researcher Observations & Comments:

>> Capture segment # ___ List major Task/Subtasks below:

(max 50 characters)

On a scale of 1 to 5, with 5 being most difficult, how would you rate that task?

(# between 1-5)

Which postures or motions did you find most difficult?

(max 50 characters)

Researcher Observations & Comments:

>> Capture segment # ___ List major Task/Subtasks below:

(max 50 characters)

On a scale of 1 to 5, with 5 being most difficult, how would you rate that task?

(# between 1-5)

Which postures or motions did you find most difficult?

(max 50 characters)

Researcher Observations & Comments:
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pg ___ of ___ Subject Feedback - Virtual Environments Lab (VEL), MSFC

use more pages if needed MSFC-VEL-Subject #:

Collected by:

Collection date:

After entire motion capture session is complete

Where there specific motions or poses that were especially challenging? Which ones?

(max 50 characters)

What difficulties did you experience while doing the tasks?

(max 50 characters)

In an ideal situation, what modified or new features would these worksites have?

(max 250 characters

Do you feel like your time in this session was well spent?

(max 250 characters

Do you have ideas for how to improve these motion capture sessions?

(max 250 characters

Analyst Summary - specific subtasks or elements described as difficult:

(max 50 characters)

List corresponding numbers or codes:

(max 50 characters)
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Appendix D. Motion Capture – User Guide and Lab Processes 
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Appendix E. Data Organization and Naming 

Table E-1. Motion Segmentation and Database Fields Worksheet (time codes, posture extraction) 
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Table E-2. Motion Segmentation and Database Fields Worksheet (element-to-task hierarchy) 
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Table E-3. Motion Segmentation and Database Fields Worksheet (.zip files downloaded per element) 
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Appendix F. NASA Program Risk Scorecard and Ratings Table 

Table F-1. Risk Scorecard with Definitions 

LIKELIHOOD RATING (LR)

5

Very 

High

Qualitative: Nearly certain to occur. Controls have little or no 

effect. 

Quantitative: 10-1<P (for risks with primary consequence on 

Human Safety - Personnel) or P>50 percent (for risks with 

primary consequence on Cost, Schedule, or Performance).

4

High

Qualitative: Highly likely to occur. Controls have significant 

uncertainties. 

Quantitative: 10-2<P≤10-1 (for risks with primary consequence on 

Human Safety-Personnel) or 33 percent<P≤50 percent (for risks 

with primary consequence on Cost, Schedule or Performance)

3

Moderate

Qualitative: May occur. Controls exist with some uncertainties.

Quantitative: 10-3<P≤10-2 (for risks with primary consequence on 

Human Safety-Personnel) or 10percent<P≤33 percent (for risks 

with primary consequence on Cost, Schedule, or Performance)

2

Low

Qualitative: Not likely to occur. Controls have minor 

limitations/uncertainties. 

Quantitative: 10-4<P≤10-3 (for risks with primary consequence on 

Human Safety-Personnel) or 1percent<P≤10 percent (for risks 

with primary consequence on Cost, Schedule, or Performance)

1

Very Low

Qualitative: Very unlikely to occur. Strong Controls in Place. 

Quantitative: P≤10-5 (for risks with primary consequence on 

Human Safety-Personnel) or P≤1 percent (for risks with 

primary consequence on Cost, Schedule, or Performance).

1 2 3 4 5

1 1 3 5 8 12

2 2 6 11 14 17

3 4 9 15 19 21

4 7 13 18 22 24

5 10 16 20 23 25

CONSEQUENCE

L

I

K

E

L

I

H

O

O
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Table F-2. Safety Ratings Table 

CONSEQUENCES 1 2 3 4 5 

 

Personnel 

Minor injury 

not requiring 

first-aid 

treatment, 

minor crew 

discomfort 

Injury 

requiring firstaid treatment, 

moderate 

crew 

discomfort 

Injury, illness or 

incapacitation 

requiring 

emergency or 

hospitalization 

treatment 

Severe injury or 

illness requiring 

extended 

hospital/Medical 

treatment

Loss of life or 

permanently disabling 

injury 

SAFETY

Facilities, 

Equipment, 

Assets 

Minor damage 

or nonessential flight 

assets 

Minor 

damage to 

Program 

Critical 

assets, Major 

damage to 

non-essential 

assets 

Minor damage to 

flight/ 

Ground assets, 

Major damage to 

Program critical 

assets, or loss of 

non-essential 

assets 

Loss of mission, 

Major damage to 

Flight/Ground 

Assets; doesn’t 

meet criteria for 

catastrophic hazard, 

or Loss of Program 

Critical Asset 

Loss of Flight/Ground 

Assets or Loss of 

vehicle prior to 

completing its mission 

 

Environmental

Negligible 

OSHA/ 

EPA violation 

– non 

reportable

Minor 

reportable 

OSHA/EPA 

violation 

Moderate 

OSHA/EPA 

violation which 

requires immediate 

remediation 

Major OSHA/EPA 

violation causing 

temporary stoppage 

Serious or repeat 

OSHA/EPA violations 

resulting in action 

terminating program 

 

Requirements 

Negligible 

impact to 

requirements/ 

design 

margins 

Minor impact 

to 

requirements/ 

design 

margins 

Moderate impact to 

requirements/design 

Major impact to 

requirements/design 

margins 

Technical goals not 

achievable with existing 

engineering 

capabilities/technologies 

PERFORMANCE

Operations 

Negligible 

impact to 

mission 

operations 

Minor impact 

to operations 

– 

workarounds 

available 

Moderate impact to 

operations – 

workarounds 

available 

Failure to achieve 

major mission 

objectives 

Contingency Abort 

 

Supportability 

Temporary 

usage loss or 

LOCM of nonflight critical 

asset 

Permanent 

usage loss or 

LOCM of 

non-flight 

critical asset 

Temporary usage 

loss or LOCM of 

major element(s) of 

flight vehicle or 

ground facility 

Permanent usage 

loss or LOCM of 

major element(s) of 

flight vehicle or 

ground facility 

Inability to support 

further flight operations 

Cost ≤$100K >$100K but 

≤$1M >$1M but ≤$10M >$10M but ≤$50M 

>$50M 

Schedule 

Negligible 

schedule 

impact 

Minor overall 

schedule 

impact (no 

impact to 

critical path) 

≤1 month impact to 

critical 

path/milestones 

>1 and ≤5 month 

impact to critical 

path/milestones 

>5 month impact to 

critical path/milestones 

or possible program 

cancellation 
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Appendix G. Database Design Structure and Software 
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Appendix H. Database Website Interface – July 31, 2013 version 

PMD Sample Pages: Element Search, Subtask Table, and Anthropometric Reference Page 
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Appendix I. Human Research Protocol and Consent Form 
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Appendix J. National Institute for Occupational Safety and Health 

(NIOSH) Lifting Equation Occupational Safety and Health 

Administration (OSHA) 

Recent OSHA polls have shown that back injuries make up as much as 33 to 38 percent of 

compensable costs in industry today1

. A result of which has been the creation of the General 

Duty Clause. The General Duty Clause’s main purpose is to force employers to provide an 

environment that is "free from recognized hazards that are causing or are likely to cause serious 

physical harm1

" to the employees. OSHA created the law in an attempt to reduce the number of 

injury incidences caused by poor lifting practices. In 1981, the NIOSH created the lifting 

equation1

. A revised version of this equation stands today as the primary tool used in 

questionable lifting applications. It represents one of the very few ergonomically measurable 

analysis tools. 

The lifting equation was first published in the NIOSH Work Practices Guide for Manual Lifting 

in 1981. The equation works by taking into account the major aspects of the lifting and carrying 

process. It is broken up into two parts, the action limit (AL) and the maximum permissible limit 

(MPL) 1. Almost every type of worker can achieve the AL whereas the MPL can only be 

achieved by a few. In terms of the working environment, an object can be lifted by virtually 

everyone until it reaches the AL. For the weights between the AL and the MPL, specifically 

trained workers must be applied. Weights that produce values beyond the MPL are not 

permitted1

. 

The AL equation (1) can be found below2. 

AL = (IW)(HF)(VF)(DF)(FF) 

Where 

IW = weight for ideal conditions 

HF = distance from the chest the object is held 

VF = distance above or below the knuckle height the object is 

being held 

DF = distance the object is being lifted to from origin 

FF = Frequency of lifting the part 

The MPL is calculated by simply multiplying the AL by 3. 
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The current standard value for IW stands at 51 pounds1. This represents the weight that most 

people could lift given completely ideal conditions. The values of HF, VF, DF, and FF can be 

found from charts and tables created by the NIOSH. Each of these values equals a number 

between 0 and 1. When one of these values is less than 1, the IW is reduced by a percentage. 

For example, consider applying the lifting equation to a current Monarch Hydraulics process. In 

the production of the M-3519 hydraulic pump, one of the workers is required to pick up a pump 

motor off the floor and walk it back to his station. The pumps come on 4×4-foot pallets. The 

pump pallets are stacked in a manner that puts the pumps at levels ranging from 

5-36 inches off the floor. The pumps are arranged on the pallet such that the distance from the 

midpoint of the worker chest ranges from 5-20 inches. A pump is picked up roughly once every 

minute and is carried approximately 10 inches above the knuckle level (approximately 40 inches 

above ground). An 8-hour workday can be assumed. To determine AL and MPL for this 

process, the dimensions that will give the worst-case scenario should be considered. From the 

NIOSH charts (Figures 14.15-14.18 and Table 14.7 of Work Design: Industrial Ergonomics 3rd

ed. by Stephen Knoz) the values are: 

HF = .3 

VF = .74 

DF = .8 

FF = .94 

Calculate AL and MPL: 

AL = (IW)(HF)(VF)(DF)(FF) 

AL = 51lbs(.3)(.74)(.8)(.94) = 8.51lbs 

MPL = 3AL = 25.53lbs 

These values for AL and MPL indicate that under the conditions stated, almost every type of 

worker can lift an 8.51lb part. The maximum weight the part can be, assuming a specially 

assigned worker, is 25.53lbs. For the Monarch application, the part weighs less then 8.51lbs and 

is within OSHA’s guidelines. 

This equation used assumes the following [ref 3]: 

o Smooth lifts 

o Lifting is done without twisting and with two hands 
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o The part being lifted is of moderate width(30 inches or less) 

o Unrestricted lifting postures 

o Good contacts(handles, shoes on floor) 

o Favorable atmosphere 

o Maximum ideal weight of 51lbs 2 

In the Monarch application, several of these assumptions may sometimes be violated. First, the 

lifting does not always include the use of both hands. It is safe to assume that at times the pumps 

are picked up with only one hand (because of the smaller size). Good contacts may be lacking 

because of no handle being present on the pump motor and oily conditions existing within the 

working environment. Twisting may also be present because of the pump supply being directly 

behind the workers position. Despite these violations, it can be assumed it is a fairly reasonable 

result. The violations mentioned would have limited impact on the final estimated weight. 

With the use of this analysis tool we have found a way to determine if a current lifting practice 

can be considered safe. The analysis tool can also be used as an improvement tool for a given 

process. A company can look at the factors that lower the weight of the Action Limit and try to 

reduce them. In the case of the Monarch example, the Horizontal Factor should be examined. If 

a scissors lift table were introduced, the resulting HF value of 1 would increase the AL to nearly 

28lbs and the MPL to 85lbs. 

To determine if the entire Monarch M-3519 process is OSHA compliant in regards to this lifting 

equation, the other assembly pieces and the completed pump will need to be analyzed. 

NIOSH Equation: Applications Manual For the Revised NIOSH Lifting Equation. U.S. 

Department of Health and Human Services (DHHS), National Institute of Occupational Safety 

and Health (NIOSH) Publication No. 94-110, (1994, January 1). Contains a complete description 

of all terms in the lifting equation with several sample calculations. 

 
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Revised NIOSH Lifting Equation 

The equation is: 

LC x HM x VM x DM x AM x FM x CM = RWL 

where LC is the load constant (23 kg) and other factors in the equation are: 

• HM, the Horizontal Multiplier factor 

• VM, the Vertical Multiplier factor 

• DM, the Distance Multiplier factor 

• FM, the Frequency Multiplier factor 

• AM, the Asymmetric Multiplier factor 

• CM, the Coupling Multiplier factor 

• RWL, the Recommended Weight Limit 

To apply the NIOSH equation to a situation of interest: 

• For each value, look up the corresponding factor and use this number in the equation. See 

Assessing Relevant Handling Factors for explanation of terms. 

• To use the calculator, click on the values for each factor in the left hand column (or you 

can input your numbers directly into the second equation). Press the "Calculate RWL" 

button when you have finished selecting all of the values. 

• HM: Horizontal distance (H, in cm) from the midpoint between the ankles to the hands 

while holding the object. 

H = Horizontal Distance (cm) HM Factor 

25 or less 1.00 

30 0.83 

40 0.63 

50 0.50 

60 0.42 
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Appendix K. Phase 2 Quick Look Test Reports 
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NESC Request No.: TI-12-00774 
NASA Engineering and Safety Center 

Technical Assessment Report 

Document #: 

NESC-RP12-00774 

Version: 

1.0

Title: 

CAD Tools to Support Human Factors Design Teams 

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NASA Engineering and Safety Center 

Technical Assessment Report 

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NESC-RP12-00774 

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CAD Tools to Support Human Factors Design Teams 

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NASA Engineering and Safety Center 

Technical Assessment Report 

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NESC-RP12-00774 

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CAD Tools to Support Human Factors Design Teams 

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NASA Engineering and Safety Center 

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NESC-RP12-00774 

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CAD Tools to Support Human Factors Design Teams 

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Technical Assessment Report 

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NESC-RP12-00774 

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NESC-RP12-00774 

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NESC Request No.: TI-12-00774 
REPORT DOCUMENTATION PAGE Form Approved

OMB No. 0704-0188

2. REPORT TYPE 

Technical Memorandum

 4. TITLE AND SUBTITLE

Computer-Aided Design (CAD) Tools to Support the Human Factors 

Design Teams

5a. CONTRACT NUMBER

 6. AUTHOR(S)

Null, Cynthia H.; Jackson, Mariea Dunn; Perry, Trey; Quick, Jason C.; 

Stokes, Jack W.

 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

NASA Langley Research Center

Hampton, VA 23681-2199

 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

 8. PERFORMING ORGANIZATION

 REPORT NUMBER

L-20417 NESC-RP-12-00774

10. SPONSOR/MONITOR'S ACRONYM(S)

NASA

13. SUPPLEMENTARY NOTES

12. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified - Unlimited

Subject Category 61 Computer Programming and Software

Availability: NASA CASI (443) 757-5802

19a. NAME OF RESPONSIBLE PERSON

STI Help Desk (email: help@sti.nasa.gov)

14. ABSTRACT

The scope of this assessment was to develop a library of basic 1-Gravity (G) human posture and motion elements used to 

construct complex virtual simulations of ground processing and maintenance tasks for spaceflight vehicles, including launch 

vehicles, crewed spacecraft, robotic spacecraft, satellites, and other payloads. The report herein describes the task, its purpose, 

performance, findings, NASA Engineering and Safety Center (NESC) recommendations, and conclusions in the definition and 

assemblage of the postures and motions database (PMD). 

15. SUBJECT TERMS

Computer-Aided Design; NASA Engineering and Safety Center; Postures and motions database; Human factors

18. NUMBER

 OF 

 PAGES

147

19b. TELEPHONE NUMBER (Include area code)

(443) 757-5802

a. REPORT

U

c. THIS PAGE

U

b. ABSTRACT

U

17. LIMITATION OF 

 ABSTRACT

UU

Prescribed by ANSI Std. Z39.18

Standard Form 298 (Rev. 8-98)

3. DATES COVERED (From - To)

April 2013 - April 2014

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

869021.05.07.01.18

11. SPONSOR/MONITOR'S REPORT

 NUMBER(S)

NASA/TM-2014-218263

16. SECURITY CLASSIFICATION OF:

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, 

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this 

collection of information, including suggestions for reducing this burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and 

Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person 

shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

1. REPORT DATE (DD-MM-YYYY)

01- 05 - 2014