Evaluation of Peripheral Visual Performance When
 

Using Incandescent and LED Miner Cap Lamps
 

John J. Sammarco, Miguel A. Reyes, John R. Bartels, and Sean Gallagher 









The authors are with the National Institute for Occupational Safety and 

Health, Pittsburgh, PA 15236 USA (e-mail: Jsammarco@cdc.gov). 

Abstract—Illumination plays a critical role in an underground 

miner’s safety because miners depend most heavily on visual cues 

to recognize hazards. Mobile mining machinery, located in the 

miner’s peripheral field of view ( 10◦ to about 60◦ off-axis), 

may pose potential pinning and striking 

±

hazards. 

±

The main objective of this research was to determine if there were peripheral 

visual performance improvements for the detection of moving 

objects when using cool-white light-emitting diode (LED) cap 

lamps as compared to incandescent (INC) light bulbs commonly 

used in miner cap lamps. The cap lamp variable of interest is the 

spectral power distribution. The illuminances were normalized by 

a diffusion filter. The second objective was to determine if age is 

a factor for the peripheral visual performance. This is important 

because the workforce is aging—the average miner age is about 

43 years old. Thirty subjects participated in the study, ten subjects 

each in the age groups of younger (18–25 years), middle (40– 

50 years), and older (51+ years). Visual performance was quantified by the subjects’ speed and accuracy of response to detect the 

rotation of high-contrast (white) circular targets located 3.83 m 

away at −20◦, 40◦, and 50◦ off-axis. The speed of detection and the 

number of missed target rotations (accuracy) were measured. The 

prototype LED cap lamp results were best with an 11%–15% improvement compared to the INC and LED cap lamps, respectively. 

Age does appear to be a significant factor. For the middle and 

older age groups, the target movement detection time increased 

75% and 60%, and the number of missed targets increased 500% 

and 450%, respectively, in comparison to the youngest age group. 

The results also suggest that target location is a significant factor. 

The subjects’ target movement detection time for the 40◦ and 

50◦ target movements increased 16% and 69%, respectively, as 

compared to the 20◦ − target. 

I. INTRODUCTION 

I LLUMINATION plays a critical role in an underground 

miner’s safety since miners depend heavily on visual cues 

to detect hazards [1]. An example of an underground hazard 

where appropriate illumination is vital is that of being struck 

or pinned by mobile mining equipment. A Mine Safety and 

Health Administration (MSHA) report [2] on remote-controlled 

continuous mining machine accidents indicated that pinning 

and striking fatalities were increasing with 12 fatalities between 

2000 and 2004, compared to 17 fatalities over the 15-year 

span between 1984 and 1999. There were 67 nonfatal striking/ 

pinning accidents from 1999 to 2004. Typically, a miner’s cap 

lamp is the primary and most important source of light for 

detecting machine movement [3], which is often located in the 

miner’s peripheral field of view (±10◦ to about ±60◦ off-axis). 

It can be very difficult for miners to detect moving machinery 

because the underground mining environment is noisy and can 

mask the audible cues given by approaching machinery; thus, 

it is critical that miners are able to detect motion in their 

peripheral field of view if they are to avoid pinning and striking 

hazards. 

Peripheral visual performance is affected by many factors 

that include the object size, reflectance, contrast, viewing distance, location off-axis, and lighting conditions. Other factors 

include a person’s age and how the human eye changes as a 

person ages. The retina of the human eye plays a critical role 

in vision [4]. The retina contains photoreceptors that convert 

light to electrical impulses that travel through the optic nerve to 

the brain. There are two types of visual photoreceptors: rods 

and cones. The rods are sensitive to light and dominate our 

night vision; the cones are sensitive to color and dominate our 

daytime vision. The rods also play a more dominant role in 

vision as light levels decrease, particularly when the lighting 

is between daylight and night. This twilight-type illumination, 

known as mesopic, is prevalent in underground mines. Rods 

assume additional importance under such lighting conditions 

as they are particularly sensitive to detecting motion in the 

peripheral field of view. 

Previous miner cap lamp lighting research investigated visual 

performance with respect to peripheral motion detection. Visual 

performance was defined as the speed and accuracy of detecting 

the rotation of cylinders (targets) located at ±60◦ and 7.66 m 

from the human subject. The research approach was to determine the relationship between visual performance and cylinder 

luminance. The results indicated that the peripheral visual performance improved 58% when target luminance was increased 

from 0.0018 to 0.15 fL [5]. 

The main objective of the National Institute for Occupational 

Safety and Health (NIOSH) research presented in this paper 

was to determine if there were visual performance improvements for the detection of moving objects in the peripheral 

field of view when using cool-white light-emitting diode (LED) 

cap lamps as compared to incandescent (INC) light bulbs 

commonly used in miner cap lamps. The second objective was 

to determine if age is a factor for peripheral visual performance 

given that there is an aging workforce. This is important to 
consider because of the aging U.S. coal mine workforce that 

has an average age of about 43 years. The research approach 

differs from prior work that increased luminance to improve 

visual performance. Our approach was to determine if peripheral visual performance could be improved by using a LED 

lamp with a visible spectrum containing more short-wavelength 

light. Recent research has indicated that, at low-light (mesopic) 

conditions, such as found in nighttime driving and underground 

mining, an increased short-wavelength spectral content can 

improve visual performance [6]. LEDs with a visible spectrum containing more of the short-wavelength light can enable 

considerable improvement in peripheral visual performance at 

mesopic conditions for automotive applications [7]. Recent 

NIOSH mining research findings indicated that, in comparison 

to INC lighting for cap lamps, cool-white LEDs with a visible 

spectrum containing more of the short-wavelengths, which 

can be characterized by the spectral power distribution (SPD), 

can enable visual performance improvements with respect to 

slip/trip/fall hazard detection, where the majority of the hazards 

are located in the peripheral field of view at ±10◦ and ±20◦ offaxis [8]. 

A. Terminology

Luminous Flux: It is the time flow rate of light energy that 

is similar in concept to horsepower or British thermal unit 

per hour. The lumen is the unit of luminous flux used by the 

Illuminating Engineering Society of North America (IESNA) 

and in the International System of Units (SI) [9]. 

Illuminance: It is the measure of the density of luminous 

flux striking a surface. The IESNA units are footcandle (equivalent to lumen per square foot) and lux (equivalent to lumen per 

square meter); the SI system only uses lux [9]. 

Luminance: In physical terms, luminance is a concept used 

to quantify the density of luminous flux emitted by an area of 

a light source in a particular direction toward a light receiver 

such as a human eye [9]. For achromatic scenes, luminance is 

correlated with a person’s perception of brightness. The most 

common IESNA and SI unit for luminance is candela per square 

meter. 

Luminance Contrast: It is the relationship between the luminance of an object and its immediate background [10]. 

SPD: It is the radiant power emitted at each wavelength in 

the visible region of light (between 360 and 770 nm). 

II. METHODS 

A. Experimental Design

A 3 × 3 × 3 (age group, light source, target location) splitsplit plot design was used in this study. The subjects represented 

the whole plots, and the whole-plot treatment was the Age 

Group. There were three Age Group categories: Group A 

(18–25 years old); Group B (40–50 years old); and Group C 

(51+ years old). The light source was the split-plot treatment 

and also had three levels consisting of the following: a commercial LED cap lamp, a commercial INC cap lamp, and a 

prototype LED cap lamp. Circular targets were positioned at 

three angles from the focal point of the subject: −20◦, 40◦, and 

50◦ (Fig. 1). 

Fig. 1. Experimental layout. 

The angle of the target location was the split-split 

plot treatment. 

Two primary dependent measures were used to examine the 

effects of the independent measures listed previously. These 

dependent measures were the following: 

1) detection time (in milliseconds) to detect target 

movement; 

2) number of target movements missed. A missed target is 

defined when the detection time exceeds 4.2 s. Thus, this 

variable was dichotomous—a trial with a missed target 

was recorded as “1,” whereas a trial with no missed target 

was recorded as “0.” 

Analysis of variance (ANOVA) was used to determine the 

significance of the main effects and interactions. The use of 

ANOVA to evaluate dichotomous variables in this study is in 

accordance with the recommendations given by D’Agostino 

[11]. Specifically, an arcsine transformation was applied to the 

proportion of trials, where missed values were obtained and 

an ANOVA was run using the transformed values. The alpha 

level for all tests was set at 0.05. Multiplicative Sidak post hoc

tests were used to determine the differences between conditions 

following a significant omnibus test. 

B. Subjects

Thirty subjects participated in the study, ten subjects each 

in the age groups of A = younger (18–25 years), B = middle 

(40–50 years), and C = older (51+ years). NIOSH personnel 

from the Pittsburgh Research Laboratory (PRL) were the subjects. Only the subjects that passed the vision tests for distance 

visual acuity, contrast sensitivity, color vision deficiency, and 

peripheral vision were accepted for the study. Miners were 

not used because of potential expectancy biases that could 

confound the empirical data. Expectancy biases are particularly challenging for lighting research because the variable of 

the study (visible light) is usually observable to the subjects. 

Miners could easily detect that the light (particularly the color) 

from the LED-based cap lamps is very different from the camp 

lamp light they use on a daily basis. 
Twenty-four male and six female subjects participated. The 

mean ages were 22.6, 47.3, and 57.6 years, respectively. The 

overall mean age was 42.5 years; the mean age of a U.S. coal 

miner is 43 years. The subjects’ peripheral vision eye test scores 

were of prime interest given the study’s focus. For the youngest 

to oldest age groups, the mean scores were 179◦, 176◦, and 

174.4◦, respectively. 

The protocol for this study was approved by the NIOSH 

Human Subject Review Board. The subjects signed an informed 

consent form and were instructed about their right to withdraw 

freely from the research at any time without penalty. 

C. Experimental Layout and Apparatus

1) MIL: 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 (dac) systems, and 

networked computers. The interior is 4.88 m wide by 2.13 m 

high and is coated with a rough-textured material that has a 

color and reflectivity of 10% which is similar to that of a coal 

mine. The experimental layout is depicted in Fig. 1. 

2) Observation Station: The observation station (Fig. 2) 

was designed to allow all human subjects to be tested at the 

same eye height with reference to the floor. 

Fig. 2. Observation station used for the human subject testing. 

The eye height of 

165.1 cm is based on the 50th percentile male standing [12]. 

The station was required to allow the test subjects ranging from 

the 5th percentile female to the 95th percentile male to be 

adjusted to the 165.1-cm eye height when in the seated position. 

Torso heights for the specified test subjects have a range of 

68.6–84.8 cm. The seat was designed to rise 20.3 cm from 

the lowest position to the highest to accommodate all the test 

subjects. The height of the miner’s helmet with cap lamp and 

earphones is independently adjustable from the seat height to 

accommodate the different torso heights of the subjects. The 

helmet height is manually adjustable (up to 25.4 cm) with handoperated clamps. The helmet adjusts fore and aft manually up 

to 15.2 cm. The seat is adjustable fore and aft and has foldable 

arm rests. 

3) Peripheral Motion Apparatus: The peripheral motion apparatus was designed to perform the dac throughout the experiment. Controlled by a dedicated laptop, the system consisted 

of both hardware and software elements which directly interacted with the human subjects being tested. The system’s main 

components were the BS2sx microcontroller, dac software, 

high-contrast (white) circular targets connected to dc-powered 

motors, and a central flip-dot matrix target. 

The system’s input was controlled using a computer mouse. 

A depressed mouse button would signal the microcontroller to 

begin the test. The microcontroller activated a flip-dot matrix, 

located at 0◦, as long as the mouse button was depressed. This 

target was used for a visual tracking task that was designed 

to draw the subject’s focus and fix their eye orientation to the 

center while the subject’s peripheral vision was being tested. 

The control system then accessed a preloaded version of software that was installed into the microcontroller. The preloaded 

software was one of four different software versions compiled 

to vary the sequence in which the three circular targets, located 

at −20◦, 40◦, and 50◦, were activated. Each version varied the 

sequence in which each target was activated a total of four 

times per test. This resulted in a cycle that included 12 target 

activations. In addition to varied sequences, the software also 

varied the initial time delay prior to each target being activated. 

Implementing time delays of 3 and 5 s created another variable 

used to ensure randomization and prevent learned behavior 

from impacting the validity of the results. The targets were 

circular in shape and had a diameter of 120 mm. Each target 

was painted a solid flat white color and had a single black line 

intersecting the center to produce a desired contrast of 0.90, 

where contrast is equal to (L1 − L2)/L1, where L1 and L2

are the respective luminances of the background and target. 

The circular targets were activated to rotate when the microcontroller supplied the required voltage to power dc motors 

on which the circular targets were mounted. Although the dc 

motors emitted noise that could have confounded the results, 

the implementation of ear protection and background noise, 

which simulated mining equipment in operation, eliminated a 

subject’s ability to use the auditory cues to identify circular 

target motion. 

The data acquisition of the peripheral motion detection experiment focused around a time-stamped Excel spreadsheet 

macro which recorded the cap lamp used, the software version 

used, the target location sequence, and the peripheral motion 

detection reaction time. The reaction time was measured from 

the time the circular target was initially activated to the time 

the subject released the depressed mouse button, signifying 

peripheral motion detection. A reaction time of 4.2 s or longer 

would be recorded as a missed target, and the next target in the 

sequence would be initiated. 

4) Cap Lamps: Three cap lamps were used. The electrical 

data for each cap lamp are listed in Table I. The first was 

an MSHA-approved cap lamp using a single INC bulb as the 

primary light source. This served as the reference. 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 NIOSH 

and the Lighting Research Center of Rensselaer Polytechnic 

Institute. This prototype uses two phosphor-white LEDs as the 

primary light source. The prototype LED cap lamp meets the 

photometric requirements specified by MSHA [13]. The cap 

lamp housing and internal components were selected to have 

a very high reflectance to mitigate discomfort glare. 

TABLE I 

CAP LAMP ELECTRICAL AND PHOTOMETRIC DATA 

Each cap lamp was characterized with respect to its SPD. 

Fig. 3 depicts the SPDs for each cap lamp.

Fig. 3. SPDs for each cap lamp as normalized at their maximum values. The 

diffusion filters, used to normalize target illuminance, were on each cap lamp. 

 It is evident that the 

LED and prototype LED cap lamps have a greater proportion of 

short-wavelength light than the INC cap lamp. Both cap lamps 

use a phosphor-white type of LED. Basically, this type is a blue 

LED with phosphor deposited on top of the die. The phosphor 

passes a portion of the blue light that mixes with the yellowishgreen emission of the phosphor; thus, the combination appears 

white to the eye. The LED cap lamp has more of the longer 

(red) wavelengths than the prototype LED due to manufacturing 

differences. Manufacturers can add secondary phosphors or 

dopants in order to have higher emission in the long wavelength 

range. 

5) Illuminance Distributions: The illuminance levels were 

measured at each object location for each cap lamp. Illuminance 

is an important factor for visual performance because, in general, visual performance increases as illuminance increases. In 

this study, it was important that the illuminance distributions be 

comparable; otherwise, major illuminance differences would be 

a confounding factor. The initial illuminance distributions had 

significant variation. For instance, the average illuminance at 

the 40◦ circular target was about 48% greater with the INC cap 

lamp as compared to that of the LED cap lamp. Therefore, a 

diffusion filter was placed over the lens of each cap lamp. This 

filter was successfully used to realize a more uniform illuminance distribution among the three cap lamps. Fig. 4 depicts the 

illuminance distributions for all circular target locations when 

using the various cap lamps with diffusion filters.

Fig. 4. Average target illuminance from each cap lamp when applying a 

diffusion filter to the cap lamps. 

 Note that the 

average illuminance at the 40◦ circular target is 3.1% less with 

the INC cap lamp as compared to that of the LED cap lamp. 

D. Procedure

Each subject was given a minimum of 15 min to adapt to 

the darkened environment of MIL. Next, a subject was seated 

on the observation station, and adjustments were made such 

that each person had the same eye height of 165.1 cm from 

the floor. While seated, the subjects wore a hard hat rigidly 

mounted to maintain cap lamp position. Eye protection was 

provided similar to that worn underground. The subjects were 

also requested to wear hearing protection to avoid possible 

auditory cues which could affect the outcomes. Additionally, 

underground mining sounds were played during the test to 

further negate possible auditory cues. Once the subjects were 

positioned and the equipment was properly adjusted, the test 

procedures were explained to the subjects. Two practice (warmup) sessions were initially conducted to help the subjects learn 

how to conduct the tests and to become familiar and comfortable with the test apparatus; this provided an opportunity for the 

subjects to ask questions on any aspect of the test they did not 

completely understand. 

The procedure was for the subject to keep their eyes focused 

on the center flip-dot matrix target in front of them during 

this entire experiment. This target consisted of a column of 

continuously flipping dots that the subjects were to watch as 

an aid to keeping their vision focused on the center of the test 

area. The subjects were instructed to use a computer mouse to 

indicate when they saw the rotation of a 12-cm disk located at 

−20◦, 40◦, and 50◦ in their peripheral field of view. Holding 

down the left mouse button started the test. The indication of the 

subject noticing the rotating disk was recorded when the mouse 

button was released. The time difference between when a disk 

started to rotate and the time the mouse button was released was 

recorded by a custom control program. The test would resume 

when the mouse button was held down again. The subjects were 

given 4.2 s to notice the change; if they did not see the change 
in less than 4.2 s, the center flip-dot target stopped changing, 

indicating that they had missed detecting one of the circular 

targets, at which point they were required to release and then 

press down the mouse button to reset and proceed with the 

experiment. 

The experiment consisted of five tests for each subject. The 

first two were warm-up tests followed by an opportunity for the 

subjects to clarify any portions of the procedure they did not 

understand. The test was then repeated for each of the three 

cap lamps: the INC and the two LED cap lamps. Each test 

consisted of a cycle of 12 random activations of the rotating 

disks in different portions of the subject’s peripheral vision. 

The experiment was then repeated with the second and third cap 

lamp following the same procedures. The order that the rotating 

disks were activated and the order in which the cap lamps were 

tested were randomized to avoid any sequencing effects in the 

data. For each age category, 50% were tested with one sequence 

of lamps and activations and the other 50% with an alternative 

sequence. 

III. RESULTS 

A split-split plot ANOVA was used to evaluate whether 

there were significant differences for the independent variables. 

Table II summarizes the ANOVA results for the detection 

time. 

TABLE II
 

ANOVA SUMMARY FOR THE DETECTION TIME
 

Note that the values of F near 1.0 indicate no effect 

for an independent variable, whereas higher values indicate a 

significant effect. The following sections detail the results for 

both dependent measures. 

A. Detection Time

All three main effects were found to significantly affect 

detection time, whereas no interactive effects were detected 

(Table II). As can be seen in the table, Age Group had a 

significant effect on detection time (F2,27 = 5.38, p< 0.05). 

The post hoc tests indicated that the subjects in Group A 

(younger subjects) had detection times that were significantly 

faster than the subjects in Group B. Differences in the detection 

time between the two older age groups were not significantly 

different. 

The use of the prototype LED resulted in significantly faster 

detection times than the commercial LED (F2,54 = 4.62, p<

0.05). On the average, the post hoc tests indicated that the prototype LED resulted in 11% and 15% faster detection times than 

the INC and commercial LED, respectively. No statistically 

significant difference in performance was found between the 

INC and commercial LED light sources. 

The angle of the flip-dot targets had a sizable impact on the 

time to detect the stimulus (F2,154 = 60.14, p< 0.001). The 

further from the center line of the subject’s line of sight, 

the greater the time the subject took to detect the stimulus. 

The 40◦ target resulted in about 16% increase in detection 

time compared to the −20◦ target, whereas the 50◦ target 

had a 76% increase in detection time. All three conditions 

were significantly different from one another according to the 

post hoc tests. 

B. Missed Targets

The results of the ANOVA on the arcsine-transformed data 

regarding missed targets indicated a significant interaction between Age Group and Target Degree (F4,8 = 6.49, p< 0.05). 

This interaction is depicted in Fig. 5 (nontransformed data), 

where the frequency of the missed targets is greatest for the 

50◦ target, typically followed by the 40◦ and −20◦ targets with 

the exception of Group A, where the −20◦ target condition 

had a slightly higher number of misses. Group B had the 

greatest number of missed targets followed by a slightly lower 

amount for Group C and a greatly reduced number of misses for 

Group A. 
Fig. 5. Occcurence of missed targets for each age group (A = younger, 

B = middle, and C = older) and for each target position (−20◦, 40◦, and 50◦). 

The error bars represent the standard error of the mean. 

IV. DISCUSSION 

The results of the visual performance comparisons between 

LED and INC cap lamps provide important data for improving 

the design of future cap lamps and should positively affect the 

safety of employees in the underground mining industry. The 

prototype LED cap lamp results were best with an 11%–15% 

improvement compared to the INC and LED cap lamps, respectively. Note the SPD differences (Fig. 3) among the three 

cap lamps. The prototype LED cap lamp’s visible spectrum 

contains more of the shorter wavelengths. The differences 

between the LED cap lamps are particularly notable at 555 nm, 

where the commercially available LED cap lamp has a much 

greater proportion of longer wavelengths in comparison to the 

prototype LED cap lamp. These results do not conclusively 

establish the superiority of LEDs for cap lamps, but they do 

suggest that LEDs with more of the shorter wavelengths, such 

as found with the prototype LED cap lamp, may offer improved 

peripheral motion detection. These results appear to be similar 

to the results of recent research, indicating that, at mesopic 

conditions, a short-wavelength spectral content can improve 

visual performance [6]–[8]. 

The lack of an interaction between age and light source 

indicates that the prototype LED cap lamp provides similar 

benefits to all age groups in terms of improving detecting 

objects in the peripheral visual field. This benefit, however, 

may be more important for middle-aged and older workers, 

whose ability to detect peripheral motion is compromised as the 

result of the aging process. However, it may be noted that, even 

with the improvement in peripheral vision with the prototype 

LED cap lamp, the toll associated with the aging process is 

often much greater. Nonetheless, the improved performance in 

peripheral vision provided by the prototype LED may help to at 

least partially ameliorate the decline associated with age. 

Such a benefit could prove to be very important for the health 

and safety of the underground miner. For example, a reduced 

capability in peripheral motion detection or perception could 

make it difficult for miners to detect moving machinery or could 

cause them to misjudge the speed that a machine is moving toward them. Any improvement in the ability to perceive objects 

moving in the periphery will convey an advantage in terms of 

being able to avoid contact with moving machinery or allowing 

quicker estimation of the speed and direction with which a 

machine is moving. 

There have been relatively few studies on the impact of 

age on motion detection and motion perception, but, for all 

age groups, people misjudge the speed of large objects which 

appear to be moving more slowly than their actual speed [14]. In 

the current study, the youngest age group had quicker response 

time compared to the older age groups, but, surprisingly, the 

older age group performed somewhat better than the middleaged group. While the difference was not statistically significant in terms of detection time, it is nonetheless unusual for 

an older age group to outperform a younger age group in 

any measure of visual performance. The reason that the older 

subject would average quicker response times is not clear, but 

it could be that the older subjects generally had better than 

average visual capabilities and the middle-aged subjects were 

below average for their age group. Thus, it is quite conceivable 

that the relatively small sample of older subjects tested in this 

study may not have been fully representative of the visual 

capabilities of the older population as a whole. Interestingly, 

the older age group also tended to outperform the middleaged group in terms of having fewer missed targets. The agerelated results indicate how important the age factor is given 

that Groups B and C had detection times that were 75% and 

60% more than Group A’s detection time. It appears that the cap 

lamp SPD is an important factor to consider for the peripheral 

visual performance of older miners given that the prototype 

LED resulted in an 11% and 15% faster detection times than 

the INC and commercial LED. 

The angle at which the targets were located also had a significant impact on detection time, with each angle being significantly different from the others. The increase in detection time 

from 20◦ off-axis to 40◦ off-axis was approximately 16%. 

Howev

−

er, the increase in detection delay between −20◦ and 50◦

was approximately 76%. Furthermore, the 50◦ target condition 

saw a tremendous increase in the number of missed targets compared to the 40◦ target condition. It is clear that even relatively 

small angular differences can make a tremendous difference 

in peripheral vision, as targets are positioned further off-axis. 

The number of missed targets generally followed this trend 

but was also dependent on the age group. We reason that the 

physiology of the human eye and the target illuminance were 

instrumental in accounting for the decreasing peripheral visual 

performance as the target angle increased. First, the greatest 

density of rods occurs between ±10◦ and ±30◦ from the retina’s 

center [4]; therefore, it would be expected that the −20◦ target 

would be detected the fastest as long as the target illuminances 

at 40◦ and 50◦ were not significantly greater. Peripheral visual 

performance will increase as the target illumination increases 

and all other factors are held constant. With respect to the 

−20◦ target, the mean target illuminance decreased about 33% 

and 48% for the 40◦ and 50◦ targets, respectively. It is very 

important to note that the target illuminances are not typical 

of actual cap lamps because a neutral density diffusion filter 

was used to normalize the target illuminances. For instance, 

the INC cap lamp’s actual target illuminance decreased about 

46% and 58% for the 40◦ and 50◦ targets, respectively, with 

respect to the −20◦ target; therefore, the peripheral visual 
performances would be poorer than those measured during this 

research. Commercially available miner cap lamps, be they 

INC or LED, typically exhibit a highly intense centralized 

beam with a total angle of about 2◦–6◦ and a relatively dim 

surround or penumbra. This centralized beam would be very 

useful for viewing distant objects or for conducting fine detail 

work tasks that require high illuminance. However, this lighting 

distribution is not conducive for detecting moving machinery 

located in the peripheral field of view. We anticipate that this 

lighting distribution will result in other detrimental effects such 

as pronounced transient adaptation effects as the miner looks 

at a very brightly illuminated object in the center beam to 

an object illuminated by much less light [5]. These issues, 

however, are beyond the scope of this paper. 

ACKNOWLEDGMENT 

The authors would like to thank T. Dubaniewicz, T. Lutz, 

M. Nelson, W. Schiffbauer, and J. Srednicki of NIOSH PRL 

for the assistance in conducting the studies described in this 

paper and M. A. Rossi, R.N., for assistance in conducting vision 

testing. 

The findings and conclusions in this paper have not been 

formally disseminated by NIOSH and should not be construed 

to represent any agency determination or policy. Mention of any 

company or product does not imply endorsement. 

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[11] R. B. D’Agostino, “A second look at analysis of variance on dichotomous 

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[12] “Human Factors Design Standard (HFDS),” USDOT, FAA, Washington, 

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[13]	 Code of Federal Regulations. Title 30, U.S. Gov. Printing Office, 

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[14] D. J Ekerdt, Ed.,	 Encyclopedia of Aging, vol. 4. Greenwich, CT: 

Macmillan Reference, 2002, p. 1467.