Visual performance for trip hazard detection when using incandescent and led miner

cap lamps

John J. Sammarco ⁎,

⁎ Corresponding author. Tel.: +1 412 386 4507; fax: +1 412 386 6710.

E-mail addresses: Jsammarco@cdc.gov (J.J. Sammarco), Sgallagher@cdc.gov

(S. Gallagher), Mreyes@cdc.gov (M. Reyes).

Sean Gallagher, Miguel Reyes

National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, 626 Cochrans Mill Road, P.O. Box 18070, Pittsburgh, PA 15236

abstract

Introduction: Accident data for 2003-2007 indicate that slip, trip, and falls (STFs) are the second leading

accident class (17.8%, n=2,441) of lost-time injuries in underground mining. Proper lighting plays a critical

role in enabling miners to detect STF hazards in this environment. Often, the only lighting available to the

miner is from a cap lamp worn on the miner's helmet. The focus of this research was to determine if the

spectral content of light from light-emitting diode (LED) cap lamps enabled visual performance

improvements for the detection of tripping hazards as compared to incandescent cap lamps that are

traditionally used in underground mining. A secondary objective was to determine the effects of aging on

visual performance. Method: The visual performance of 30 subjects was quantified by measuring each

subject's speed and accuracy in detecting objects positioned on the floor both in the near field, at

1.83 meters, and far field, at 3.66 meters. Near field objects were positioned at 0 degrees and ±20 degrees off

axis, while far field objects were positioned at 0 degrees and ±10 degrees off axis. Three age groups were

designated: group A consisted of subjects 18 to 25 years old, group B consisted of subjects 40 to 50 years old,

and group C consisted of subjects 51 years and older. Results: Results of the visual performance comparison

for a commercially available LED, a prototype LED, and an incandescent cap lamp indicate that the location of

objects on the floor, the type of cap lamp used, and subject age all had significant influences on the time

required to identify potential trip hazards. The LED-based cap lamps enabled detection times that were an

average of 0.96 seconds faster compared to the incandescent cap lamp. Use of the LED cap lamps resulted in

average detection times that were about 13.6% faster than those recorded for the incandescent cap lamp. The

visual performance differences between the commercially available LED and prototype LED cap lamp were

not statistically significant. Impact on Industry: It can be inferred from this data that the spectral content from

LED-based cap lamps could enable significant visual performance improvements for miners in the detection

of trip hazards.

1. Introduction

Approximately 619,000 people (U.S. BLS, 2008a) are employed,

directly and indirectly, in the United States mining industry. Coal

mining is of particular importance to the U.S. economy given that

coal-fired electrical generation plants provide about 57% of the

electricity for the United States. Proper lighting is critical for miner

safety, particularly in underground mines, as miners depend heavily

on visual cues to see mine hazards that include slip, trip, and fall (STF)

hazards (Cornelius, Steiner, & Turin, 1998). A main conclusion from a

study addressing the role of mine illumination in reducing risk was

that a number of STF accidents could have been avoided if proper

lighting was provided (Rushworth, Talbot, Von Glehn, Lomas, & Franz,

2001). Foster's (1997) analysis of mining risks stated that lighting

improvements could reduce mine STF accidents. Our analysis of Mine

Safety and Health Administration (MSHA) accident data for 2003-

2007 indicates that for underground mining, STFs are the second

leading accident class (17.8%, n= 2,441) of lost-time injuries. For

2003-2007, STFs resulted in 158,861 non-fatal days lost of work for

underground mining operations (MSHA, 2007). The 17.8% distribution of STFs for mining are quite comparable to that of private

industry, where STFs are a leading event for injury and account for

17.7% of all non-fatal occupational injuries (U.S. BLS, 2007). However,

mining STF accidents are not unique to the United States. An analysis

of British coal mining accidents indicated that STF accidents occurred

more frequently than any other accident category (Foster, 1997).

About 49% of these STF accidents occurred while walking and not

carrying any objects.

The underground mining environment is dynamic and harsh and

poses significant challenges in terms of detecting STF hazards. The

mine layout changes as mining progresses and machinery is moving

throughout the environment. Floor conditions can degrade due to
material that has spalled from the walls, fallen from the ceiling, or

from moving machinery. For coal mining, the environment is of low

reflectivity and low contrast. As a result, objects associated with slip,

trip, and fall hazards are also typically of low contrast and reflectivity.

Mine floors are often uneven and can be wet or contain standing

water with submerged tripping hazards. Mine lighting is limited, thus

making it more difficult for miners to see hazards. Mesopic conditions

(low lighting) are typical. Often, the only lighting a miner has is from a

battery-powered cap lamp worn on the miner's helmet. Traditionally,

miner cap lamps used an incandescent bulb as the light source. Today,

light-emitting diode (LED) light cap lamps are gaining acceptance and

seem poised to supplant incandescent lighting technology.

Prior safety research involving mine lighting aimed to improve

safety by increasing the light output. It was noted that overall accident

rates decreased as much as 60% when the overall illumination was

increased (Sanders & Peay, 1998). Other researchers noted dramatic

increases in the ability of miners to see loose rock as illuminance

increased from 500 to 1500 lux (Trotter & Kopeschny, 1997).

Research, specific to the lighting of underground metal/nonmetal

mines, determined that increasing the illuminance could improve

visual performance for detection and recognition of trip hazards

(Merritt, Perry, Crooks, & Uhlaner, 1983). The strategy of increasing

overall illumination has shown to improve visual performance and

safety; however, this strategy has the undesirable consequences of

increasing disability glare and increasing the electrical power drain on

battery-powered lighting.

The primary objective of this study was to determine if new LEDbased cap lamp technology has an impact on visual performance in

the context of detecting trip hazards for the visual environment of an

underground coal mine. Our approach was to focus on improving the

spectral content of light rather than increasing illumination. The

spectral sensitivity of the eye for mesopic (twilight) conditions differs

from that of photopic conditions (daylight) in that the eye is more

sensitive to the shorter wavelengths of visible light. Some LEDs,

classified as cool white, have more short-wavelength energy thus

giving the appearance of bluish-white light versus traditional warmwhite incandescent bulbs that emit a yellowish light and have more

longer-wavelength energy. Prior research findings indicated that light

having more short-wavelength energy enables improved detection of

off-axis objects when the visual environment is mesopic (He, Rea,

Bierman, & Bullough, 1997; Van Derlofske, Bullough, & Watkinson,

2005; Bullough & Rea, 2000). Results from a pilot study investigating

visual performance for detecting mine trip hazards indicated that

there was merit in using LEDs having more short-wavelength energy

(Sammarco & Lutz, 2007). A secondary objective of this research was

to determine the affect of aging on visual performance in mesopic

conditions, especially with respect to these lighting technologies.

Mesopic conditions pose additional visual challenges for older people.

This is an important factor given an aging U.S. coal mining workforce

that averages about 46 years old (U.S. BLS, 2008b). The physiology of

the human eye is such that visual performance degrades as a person

ages. These physiological changes include reduced pupil size, cloudier

lenses, and reduction in the amount of rod photoreceptors that play

a dominant role in vision as light levels decrease. These factors may

all have a significant impact on visual performance at mesopic

conditions.

2. Methods

2.1. Subjects

National Institute for Occupational Safety and Health (NIOSH)

personnel from the Pittsburgh Research Laboratory (PRL) were the

subjects. None were specifically involved with this cap lamp research,

and most of the subjects were not familiar with miner cap lamps or

they had used them infrequently. Only the subjects that passed vision

tests for distance visual acuity, contrast sensitivity, and peripheral

vision were accepted for the study. Subjects that had radial

keratotomy, monocular vision, glaucoma, or macular degeneration

were excluded. Miners were not used because of potential expectancy

biases that could confound empirical data. Miners could immediately

determine that the bluish-white light from an LED cap lamp is very

different from the yellowish light of an incandescent cap lamp; thus a

negative bias could exist because the light is not what they are

accustomed to, or a positive bias could exist if the person perceives

something new as better.

Twenty-four male and six female subjects participated. While

gender was not a variable in this study, given that visual performance

is not dependent on gender, the percentage distribution for gender is

representative of the U.S. miner population. Three age categories were

established and each had 10 subjects: Group A= 18 to 25 years old,

Group B= 40 to 50 years old, and Group C= 51 years old and over.

The average ages where 22.6 years, 47.3 years, and 57.6 years,

respectively. The average age of all participants was 42.5 years This

is representative of the average U.S. coal miner's age of 46 years.

Subjects signed an informed consent form and were instructed

about their right to withdraw freely from the research at any time

without penalty. The protocol for this study was approved by the

NIOSH Human Subject Review Board.

2.2. Experimental Design

A within-subjects design was employed in this study. Presentation

of cap lamps were randomly assigned to subjects and a restricted

randomization was used for stimulus order presentation within cap

lamps. Due to the expected presence of censored observations (i.e.,

trials where subjects would not be able to identify all objects in the

given time-frame), a Cox regression analysis was employed. Cox

regression is considered a full-information technique for data

containing censored observations (Klein & Moeschberger, 1997). A

number of covariates were investigated for inclusion in the model.

The following independent variables were investigated:

• 3 Age categories: Group A= 18-25 years old; Group B= 40-50 years

old; Group C= 51+ years old.

• 3 Cap lamp sources: LED cap lamp, Incadescent cap lamp, and a

Protoype LED cap lamp;

• 4 Object patterns (Fig. 1).

Fig. 1. The four object patterns: (1) near field; (2) mixed; (3) mixed; (4) far field.

Each independent variable was coded using indicator variables.

For Age Group, Group A (young subjects) was treated as the referent

category. For cap lamps, the incandescent cap lamp (the traditional
cap lamp used in mining) was chosen as the referent. Finally, object

pattern number 1 was chosen as the referent condition among the

four object patterns. Selection of the latter referent category was

somewhat arbitrary; however, authors wanted the referent category

to have a mix of near and far field objects because this would be

encountered in a mine. All 2-way and 3-way interactions between

these variables were also tested for inclusion in the model.

Significance of the model for each step of the forward selection

procedure was determined using Likelihood Ratios. Wald statistics

were used to detect differences between specific levels of a variable.

The proportional hazards assumption was tested for each successive

block in the model building process. DfBetas were run as a diagnostic

to examine estimated changes in coefficients if a case were to be

removed.

The primary dependent variable was the time taken to detect all of

the objects presented. Trials in which objects were not all located

during the allotted time were treated as right-censored observations.

Alpha levels were established at 0.05 for variable inclusion in the

model. In interpreting the results of the risk ratios (RRs) generated in

the survival analysis, it should be noted that in many survival analysis

studies, the event of interest has a negative connotation (death, for

example). In such studies, a higher RR for a factor conveys a higher

risk of a negative event happening. In the current study, however, the

event of interest is positive in nature. The event in this study consisted

of finding all of the objects presented (a good thing). Thus, a higher

reported RR in our study indicates a situation where more rapid

detection of the STF objects was achieved (i.e., a higher RR denotes a

benefit and a lower RR represents poorer performance).

3. Experimental layout and apparatus

3.1. Mine Illumination Laboratory

The testing was conducted at the Mine Illumination Laboratory

(MIL) of NIOSH PRL. The MIL is a simulated, underground coal mine

environment that is equipped with various test equipment, data

acquisition and control systems, and networked computers. The

interior is 488 cm (192 in) wide by 213 cm (84 in) high and is coated

with a rough-textured material that has a color and spectral

reflectivity representative of a coal mine.

3.1.1. Observation Station

It was important to have each subject at a fixed, known coordinate

with respect to the test apparatus, and to have each subject's position

fixed so that their point of view was the same regardless of their body

size. This eliminated data confounding from variations in the subjects'

point of view. Hence, NIOSH personnel designed and constructed an

observation station (Fig. 2) to enable each subject to be tested at an

eye height of 165.1 centimeters (cm).

Fig. 2. The observation station.

This eye height, with reference

to the floor, was based on the 50th percentile standing male (USDOT,

2003). Seat height was controlled using electric actuators and the seat

was designed to accommodate testing of subjects ranging from the

5th percentile female to the 95th percentile male. The height of the

miner's helmet was independently adjustable from 68.6 cm to

84.8 cm to accommodate varying torso lengths. The observation

station and all of its components were painted a flat black color to

eliminate reflections and to prevent distractions during testing.

3.1.2. Cap Lamps

Each cap lamp was brand new and was powered using a regulated

power supply rather than a cap lamp battery to eliminate voltage

fluctuations as the battery discharged. The power supply voltages for

the cap lamps were set according to the specifications for the

particular make and model of cap lamp. These voltages were

representative of fully-charged batteries. The first cap lamp was

MSHA-approved and used a single incandescent bulb as the primary

light source. This served as the referent cap lamp. The second was an

MSHA-approved cap lamp with a single phosphor-white LED as the

primary light source. The third cap lamp was a laboratory prototype

that was jointly developed by the Lighting Research Center of

Rensselaer Polytechnic Institute and NIOSH. This prototype uses two

phosphor-white LEDs as the primary light source. The prototype LED

cap lamp meets the photometric requirements specified by MSHA

(Code of Federal Regulations [CFR] 30, 2005). The application of

diffusion filters was necessary to normalize the light output for each

cap lamp because initial illuminance distribution measurements

revealed significant variations among the trip objects. For example,

preliminary measurements indicated that the illuminance of certain

objects was about 42% less with the prototype LED cap lamp than with

the incandescent cap lamp. Controlling the object illuminance

distributions throughout the experiments ensured that the lighting

research was contained to the spectral content of the cap lamps rather

than a combination of several underlying factors that would confound

the data. Each cap lamp was characterized in terms of its electrical

data and its spectral power distribution (SPD) (Fig. 3). The cap lamps'

electrical and photometric data are listed in Table 1. Both LED cap

lamps use a cool-white type of LED characterized by a correlated color

temperature (CCT) between 5000 K and 10000 K. The incandescent

cap lamp light source is categorized as warm white having a CCT that

is typically 2600 K to 3700 K.

3.1.3. Experimental Layout

The general layout is depicted in Fig. 4. A motorized curtain was

installed .91 m in front of the observation station to prevent the

subject from gaining an advantage in finding the objects while the

researcher changed object location patterns. This curtain was

connected to a microcontroller programmed to control the curtain

and time the duration of each test. Two location categories were

established for this experiment: near-field 1.83 meters (m), about the

distance of two strides for the average male, and far-field 3.66 m, a

common visual attention location for a walking person. Table 2 lists

the near-field and far-field illuminances. The objects were made from
sections of PVC electrical conduit. Each object (Fig. 5) was 6.4 cm long

with a 3.3 cm outer diameter and 2.2 cm inner diameter. The objects

were painted a dark color such that they would have a very low

contrast (-0.11 to 0.09) and a reflectivity (5%) very similar to an object

that was coated with the material on the coal mine floor. Four object

location patterns were presented (Fig. 1) to each subject: (1) two

objects in the near field; (2) two objects in near and far field; (3) two

objects in the near and far field; (4) two objects in the far field.

Fig. 3. The spectral power distributions for each cap lamp.

3.2. Procedure

The subjects sat in a darkened environment for 15 minutes to

enable retina dark adaptation. Next, subjects were seated on the

observation station and adjustments were made such that each

person had the same eye height of 165.1 cm (65 in) from the floor.

While seated, the subjects wore a miner's hardhat with a cap lamp.

The procedure was to close the black, electrically-powered curtain

and arrange objects according to the corresponding object patterns

selected for each subject. The presentation order for the four object

location patterns of Fig. 1 was counterbalanced. The subjects were

instructed to point at each object using a laser pointer and count it out

loud when the curtain opened. Prior to the test, subjects were told

how many objects would be in the visual scene because pilot testing

revealed that some subjects would stop the test before all objects

were found or some subjects continued to search for objects although

all objects were detected. When the subject was ready, the curtain

was opened and the PC-based data acquisition system started

recording time. The curtain was closed once all objects were detected,

or after a 10-second period expired. The time was recorded when the

last object was detected or the 10 second period expired. If a subject

did not detect an object, the object location and pattern were

recorded.

Table 1

Cap lamp electrical and photometric data.

Cap Lamp Electrical Characteristics Photometric Characteristics

Voltage Current Power Peak Correlated color

(Vdc) (amps) (watts) wavelength (nm) temperature (K)

Incandescent 4.0 0.63 3.84 780 2880

Commercial 6.0 0.42 2.56 448 5855

LED

Prototype 8.0 0.113 1.56 444 6844

LED

4. Results

Results of the Cox regression analysis can be found in Table 3. The

analysis indicated that object pattern was the most influential factor

in terms of detection time, followed by the type of cap lamp used and

then age group. No significant interactions were detected. The

proportional hazards assumption was satisfied for both cap lamp

and age group effects; however, hazards related to the object patterns

were found to change with respect to time. This necessitated inclusion

of an interaction term between the object factor and the natural

logarithm of time in the model, as reflected in Table 3. No cases were

found to exert undue influence on the results.

Table 4 provides survival times at the mean of the covariates for

object patters, cap lamp, and age group. As can be seen in this Table,

object pattern 4 (objects all in far field) was associated with the most

rapid detection of the STF objects, on average. Object patterns 2 and 3

(where objects were placed in both near and far field locations) were

found to result in increased detection time, on average. Object pattern 1

(objects all in near field) was associated with the second fastest

detection.

In the comparison of cap lamp effects, both LED cap lamps

(prototype and commercially available) led to more rapid detection of

objects compared to the traditional incandescent cap lamp (pb0.001).

Fig. 6 illustrates survival functions for the three cap lamps employed

in the study. As can be seen, the incandescent cap lamp was associated

with a consistently higher cumulative survival curve (indicative of

increased time required to detect objects) compared to the LED cap

lamps, which resulted in very similar performance. Using the INC cap

lamp as the baseline for comparison, the prototype and commercial

LED cap lamps respectively resulted in 12.7% and 14.4% faster

detection times than the incandescent cap lamps. The prototype

LED resulted in slightly slower detection time than the commercial

LED cap lamp; however, the difference was not statistically significant.

The LED-based cap lamps enabled detection times that were an

average of 0.96 seconds faster.

The middle age group was found to have increased detection times

compared to younger subjects (Pb0.01). However, the older age

group had detection times not significantly different from the young

age group (pN0.05).

5. Discussion

5.1. Object Location

The location of objects on the floor, the type of cap lamp used, and

the age of the subject all had significant influences on the time

required to identify potential STF hazards. In terms of object location,

subjects were able to most rapidly identify objects when they were all

in the far field and it took significantly longer for subjects to identify

objects in the near field. This may have been the result of a slight

increase in the average far-field illuminance as compared to the

average near-field illuminance that was about 9.7% less. The search

strategy may have played a role given that the far-field would be a

more natural visual attention location as compared to near field.

However, the longest detection times were found to take place when

subjects had to search for both near and far field objects during a trial.

This is likely the result of the search strategy subjects used to locate

the STF objects and that four objects were to be detected rather than

two objects for near or far-field tests.

5.2. Cap Lamps

Compared to the incandescent cap lamp that is current standard in

the mining industry, the LED cap lamps resulted in detection times

that were, on average, more than 0.96 seconds faster. As seen in

Table 4, the prototype resulted in slightly more rapid mean detection
time; however, the difference was not significantly different compared to the commercial LED cap lamp. We infer from the results that

the LED cap lamps enabled better visual performance because of the

spectral content: the LEDs were cool white that have more of the short

wavelengths compared to the warm-white incandescent cap lamp. It

is important to note that the results do not infer that all types of LEDs

will enable visual improvements because there are various categories

of white LEDs available: neutral-white LEDs have less short

wavelengths (CCT is typically 3700 K to 5000 K) and warm-white

LEDs have CCTs similar to incandescent lamps. Although our results

indicate the importance of special content for visual performance, the

levels of illuminance, contrast, and object size are other factors of

importance. Note that the illuminances (average near and far-field

illuminances of 1.21 lux and 1.43 lux, respectively) are very low with

respect to illuminance levels for safety that have been established for

hazards requiring visual detection. When there is a high degree of

hazards requiring visual detection, the absolute minimum illuminance level is 22 lux when activity levels are low and 54 lux when

activity levels are high. This value should be increased if the effective

reflectance of the ceiling, walls, and floor are less than 0.5, 0.1, and 0.1,

respectively (Rea, 2000). Typically, coal has a reflectance of .03 or .04

so the recommended illuminances should be increased. In general,

visual performance increases with increases in illuminance. Thus, we

anticipate that significant visual performance improvements would

be realized if the cap lamps provided the recommended illuminance

for safety.

Fig. 4. The experimental layout.

5.3. Subject Age

Younger subjects were able to detect objects significantly faster

than the middle age group. Surprisingly, the older age group was not

significantly different from the young age group in terms of detection

time (though the older group's average was half a second slower than

the young age group, on average). One would anticipate a constant

deterioration in performance with increasing age. The current

findings may be the result of sampling older individuals with better

than average vision and/or a middle-age cohort with poorer than

normal vision. This possibility is supported by the fact that in a study

of peripheral motion detection using the same sample, the older age

group also performed somewhat better than the middle-age group

(Sammarco, Reyes, Bartels, & Gallagher, 2008). Given the substantial

amount of research showing progressive decrements in visual

performance with age, one might fairly question whether the current

results would be replicated in future samples.

Table 2

Average Near and Far-Field Illuminances.

Location Average vertical illuminance (lux) with diffusion filter Average vertical illuminance (lux) without diffusion filter

Incandescent Commercial LED Prototype LED Incandescent Commercial LED Prototype LED

Near-field 1.28 1.17 1.17 0.68 0.38 0.29

Far-field 1.27 1.49 1.26 1.06 0.94 0.56

5.4. Visual Performance

Visual performance was defined as the speed and accuracy of

detecting trip hazard objects; thus, visual performance is a function of

time so the results could vary given the time duration of each

experiment. A 10-second time limit was imposed to bound the

experiments. The selection of this time was subjective given the visual

task. The data analysis and results described in this paper were strictly

bound to the 10-second time limit; however, data collection

continued. Analysis of all the collected data yielded the same result

in that the LED-based cap lamps enabled visual performance

improvements, and that there was not a statistically significant

difference between the LED-based cap lamps. The magnitude of

improvement did change. The prototype LED cap lamp enabled the

fastest average detection time that was 14.4% faster than the

incandescent cap lamp. Collectively, the LED-based cap lamps enabled

detection times that were an average of 0.96 seconds faster as

compared to the incandescent cap lamp. Given an average walking

speed of approximately 1.5 m/s suggest that that the quicker

detection of objects that may cause slips, trips, or falls may allow

enough increased time and distance for a miner, using an LED cap

lamp, to avoid hazards that might be in his path.

5.5. Limitations

Two main limitations of this study existed. The testing was

conducted in a laboratory environment that closely emulated an

underground coal mine; but it did not include factors such as wet floor

conditions or the presence of airborne dust. Additionally, the subjects
were stationary when tested and each person's viewpoint was fixed

by seating them in the observation station and adjusting for the same

eye height from the floor. While this test situation reduced the

likelihood of data confounding and the tripping risks associated with

subjects walking in a dark area, it did not emulate typical activities

such as walking. Although the subjects were not miners, we do believe

this reduced potential expectancy biases that could confound

empirical data. Our experiences, while anecdotal, suggest that these

expectancy biases are likely. Some miners with many years of

experience with incandescent cap lamps initially do not like the

light from LED cap lamps, while relatively new miners feel they can

see better. The second limitation is that the cap lamps functioned at

optimal performance given the ideal conditions of fully-charged

battery power and new light sources. Our research has indicated that

there are significant differences between INC and LED cap lamps for

real-world conditions and that LEDs have significant advantages that

include significantly less spectral composition shift, and more

constant light output as the battery discharges due to the electronic

drive circuitry commonly used for LEDs (Sammarco, Freyssinier,

Zhang, & Bullough, 2008). Additionally, after aging the INC bulb, the

light output decreased about 35% while over the same aging condition

the LED light output decreased about 3%. Generally, visual performance decreases as the light output decreases and when the spectral

content contains more of the longer wavelengths; thus, it is

reasonable to expect that the visual performance improvements,

enabled by LEDs, would be even greater than the INC cap lamp under

real-world conditions. Lastly the spectral content of cap lamp light

was the independent variable; so the likely visual performance

improvements from increasing cap lamp luminance is unknown.

Fig. 5. A test object.

Table 3

Final Cox regression model.

B SE Wald df Sig. RR 95.0% CI for Exp(B)

Lower Upper

Object Pattern 76.707 3 .000

Object Pattern 2 -3.824 .900 18.065 1 .000 .022 .004 .127

Object Pattern 3 -3.551 .895 15.742 1 .000 .029 .005 .166

Object Pattern 4 3.576 .743 23.144 1 .000 35.720 8.322 153.315

Cap lamp 14.367 2 .001

Commercial LED .514 .139 13.633 1 .000 1.673 1.273 2.198

Prototype LED .383 .141 7.355 1 .007 1.467 1.112 1.934

Age 13.364 2 .001

Middle Age -.504 .138 13.364 1 .000 .604 .461 .791

Group

Older Age -.238 .138 2.989 1 .084 .788 .602 1.032

Group

Object*T_COV_ 52.321 3 .000

Object Pattern 1.932 .486 15.828 1 .000 6.905 2.665 17.890

2*ln(time)

Object Pattern 1.738 .482 12.986 1 .000 5.684 2.209 14.624

3*ln(time)

Object Pattern -1.777 .483 13.554 1 .000 .169 .066 .436

4*ln(time)

5.6. Impact on Industry

The results of our study indicate that the spectral content of coolwhite LED cap lamps could enable visual performance improvements

for the detection of trip hazards in mesopic conditions typically

encountered in underground coal mines. These results could prove

useful for other industrial applications where trip hazards exist in a

visual environment characterized to be within the mesopic luminance

region.

Table 4

Survival times at the means of model covariates.

Variable Condition Mean time to SE 95%CI

detection (S)

Object Pattern 1 6.337 0.265 5.817 – 6.856

Pattern 2 7.556 0.210 7.138 – 7.994

Pattern 3 7.696 0.231 7.243 – 8.148

Pattern 4 4.298 0.238 3.832 – 4.763

Cap lamp Incandescent 7.116 0..244 6.637 – 7.595

Prototype LED 6.217 0..227 5.744 – 6.690

Commercial LED 6.089 0.139 5.645 – 6.533

Age Group Young 5.972 0.237 5.508 – 6.436

Middle-age 6.954 0.245 6.474 – 7.434

Older 6.496 0.233 6.039 – 6.954
Fig. 6. Survivorship functions for the cap lamps. 6. Disclaimers

Mention of any company or product does not constitute

endorsement by NIOSH. The findings and conclusions in this report

are those of the authors and do not necessarily represent the views of

the National Institute for Occupational Safety and Health.

Acknowledgements

The studies described in this paper were conducted with

assistance from T. Dubaniewicz, T. Lutz, M.E. Nelson, A. Podlesny, J.

Srednicki, and L. Williams of NIOSH PRL. Vision testing was conducted

by M. A. Rossi R.N.

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John J. Sammarco, Ph.D., P.E. is a Senior Research Engineer with the National Institute

for Occupational Safety and Health. His Federal service has been devoted to mine

safety research in a wide variety of areas including mining machine navigation and

guidance, control systems, and sensors. His recent research areas concern system

safety, hazard/risk analysis of processor-controlled mining systems, smart wireless

sensors, visual performance, and solid-state lighting systems for mine applications.

Sean Gallagher, PhD, CPE: Since 1984, Dr. Gallagher has performed research to reduce

musculoskeletal disorder risk in the mining industry, initially with the United States

Bureau of Mines and subsequently with the National Institute for Occupational Safety

and Health. A major interest has been to quantify the physical demands associated

with work in the underground coal mine environment and the biomechanical and

physiological effects of working in restricted work spaces. He received his PhD in

Industrial and Systems Engineering at the Ohio State University in 2003. His

dissertation examined the tolerance of the lumbar spine to repeated loading during

lifting in forward bending postures.

Miguel A. Reyes is a Research Engineer with the National Institute for Occupational

Safety and Health. His areas of research include wireless mine communications, mine

tracking systems, miner proximity warning systems, and solid-state lighting systems

for mine applications.