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A portable device for the assessment of dynamic visual acuity
Applied Ergonomics 41 (2010) 266–273
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A portable device for the assessment of dynamic visual acuity Janan Al-Awar Smither a, *, Robert S. Kennedy b a b
Department of Psychology, University of Central Florida, Orlando, FL 32816-1390, USA RSK Assessments, Inc., Orlando, FL, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 January 2008 Accepted 24 July 2009
Dynamic visual acuity (DVA) thresholds are among the few visual functions predictive of automobile crashes. DVA is also sensitive to alcohol and aging. However, measuring DVA is awkward because there is no standardized, efficient, flexible apparatus for DVA assessment. In this project, we developed a prototype of an automated, portable DVA system using a low-energy laser, and we compared this laser DVA with the traditional device in two within-subjects, repeated measures designs. The two studies included 48 participants (22 males and 26 females with an average age of 18.33 years). The most important findings were that: (1) retest reliabilities of the two DVA devices were comparable and higher with the laser; (2) average correlations between the two devices were r ¼ 0.62 (p < 0.01) and r ¼ 0.65 (p < 0.01) for the two designs respectively; and (3) after correction for reliability attenuation these improved to r ¼ 0.92 and r ¼ 0.78. These findings indicate that a flexible DVA laser device can be developed to measure the same construct as the more traditional bulky DVA device. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: Dynamic visual acuity Visual screening Portable DVA
1. Introduction Dynamic visual acuity (DVA) has had an impressive research history which suggests that it represents a possible visual functioning screening and classification system largely untapped by the military and private sectors. A common complaint raised repeatedly throughout the 50-year history of DVA research has been the concern that there is no standardized, efficient, flexible apparatus for DVA assessment. In our effort we sought to determine the feasibility of designing such an apparatus by showing comparability with a standard test. We also assessed the feasibility of using laser and computer technology to implement menu-driven production of targets and prototypes of specified sizes, velocities, optotypes, and motion-types in a manner that may be readily tailored to a researcher’s needs, or to the particular demands of a clinical or vocational setting in which the instrument is used. 1.1. General history of DVA The empirical history of DVA is usually traced to the work of Ludvigh at the end of WWII (see Miller and Ludvigh, 1962; Morrison, 1980; Hoffman et al., 1981). Ludvigh first reported the dramatic fall-off in acuity as target velocity was increased to even modest levels and he described this relationship with a simple exponential * Corresponding author. Tel.: þ1 407 823 5859; fax: þ1 407 823 5862. E-mail address: [email protected] (J. Al-Awar Smither). 0003-6870/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.apergo.2009.07.008
function, y ¼ a þ bx3 (where y is threshold target size, a and b are empirically-determined parameters, and x is target velocity). Since Ludvigh’s early work, two factors have provided the continued interest in DVA. First, DVA is not predictable solely from static acuity. There is only a modest correlation between static acuity and DVA, and even this tends to disappear as target velocity exceeds approximately 60 /s (Morrison, 1980). This suggests DVA, which requires precise oculomotor functioning in addition to optical and neural resolution, is not revealed by a determination of traditional acuity alone. More recently, research has shown that DVA is also unrelated to observers’ contrast sensitivity (Long and May, 1992). Second, DVA appears to be related to many real-world activities more strongly than is static acuity. As the Committee on Vision of the National Research Council (1985) has reviewed, higher DVA performance in the laboratory has been associated with both lower driving crash rates (Burg, 1967, 1968, 1971; Henderson and Burg, 1973; Shinar, 1977) and certain in-flight performance measures for pilots (DeKlerk et al., 1964). It is critical to note that these relationships exist among individuals who have been prescreened for good static acuity (minimum 20/25). 1.2. Relationship between DVA, alcohol, and aging DVA can be conceptualized as a global or composite measure of oculomotor visual functioning (Committee on Vision of the National Research Council, 1985; Morrison, 1980; Hoffman et al., 1981). DVA is presumed to reflect the integrated functioning of
J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273
optical, sensory, and motor components of the visual system and it is clearly required for many real-world activities in a dynamic setting. DVA is more likely a factor in the reduced performance related to alcohol or aging effects than is traditional static visual acuity. Schma¨l et al., (2003) found that alcohol significantly increased latency no matter the subjects’ levels of alcohol consumption. Ishihara et al. (2004) found similar decrements in elderly individuals. The relative contributions of the underlying components (e.g., saccadic latency, saccadic accuracy, saccadic frequency, pursuit accuracy, optical clarity, neural channel sensitivity, etc.) need not be formally specified for the global DVA measure to prove useful for the evaluation of alcohol or aging effects applied to contexts such as driving. The practical difficulties of assessing many of these factors separately in an applied context are effectively avoided. The relevance of alcohol’s effects on DVA for the proposed research program can be summarized succinctly: (a) an individual’s DVA cannot be predicted from the assessment of his/her static acuity; (b) DVA has been reported to be significantly correlated with driving performance (and other applied tasks); and (c) even low-moderate levels of alcohol can degrade DVA. Although a 20/40 criterion may be adequate to obtain a driver’s license, individuals may differ markedly in their visual capacity to resolve or discriminate objects once they are in motion. This clearly suggests that current static vision tests for licensing drivers are incomplete, particularly in terms of testing drug/alcohol users, the elderly, and individuals with a variety of ocular problems and pathologies. Development of a valid and reliable DVA test would represent a major contribution as an ‘‘emerging technology’’ for more accurate and reliable assessment of critical dynamic visual acuity functions to serve as a predictor of visual requirements in many real-world settings, particularly driving. There is a little question concerning age and its effects on DVA. Several studies have demonstrated severe degradation in DVA performance with increasing age after about the fourth decade. Burg’s famous DVA work (1966) with a sample size of 17,500 participants ranging in age from 16 to 92 years has provided a powerful picture of an age-dependent decline in visual performance. Subsequent DVA studies have reaffirmed these results under differing conditions and procedures (e.g., Farrimond, 1967; Ishigaki and Miyao, 1994; Long and Crambert, 1990; Reading, 1972a, b). Very importantly, it should be noted that this age-dependent decline in DVA performance is evident even when the elderly participants are prescreened for minimum static acuity levels of 20/40. Clearly, the drop-off in DVA performance with advancing age is not dependent or predictable from changes in static acuity levels alone. Moreover, these results are consistent with reports of an age-dependent decline in eye movement efficiency revealed from direct eye movement recording (e.g., Sharpe and Sylvester, 1978; Spooner et al., 1980). Recently, Kennedy et al. (1996) showed age-related performance in saccadic accuracy and other temporal factors tests in a small (N ¼ 25) group of participants aged 35–75. Given the important role DVA can play in the performance of real-world tasks, and the fact that currently there is no standardized, efficient, and flexible apparatus for DVA assessment, the aim of this research was to develop a reliable, automated and portable DVA device to serve as a predictor of visual requirements in many real-world settings, particularly driving. 2. Method 2.1. Apparatus The first objective was to construct a DVA device that would be portable and easy to use. This device also needed to compare
267
favorably with the traditional DVA device. The plan was to assemble a facsimile of the original device, then conduct repeated measures, within-subjects empirical tests with the new and old devices, and then compare whether the two apparatuses measured the same visual process and, if so, how well the new device measured DVA. 2.1.1. Projection screen A screen was constructed using a highly reflective (>80%) flexible whiteboard material which provided an effective viewing area of 46.6 to either side of center for a total view angle of 93.2 forward as situated from the chin rest which ensured proper head positioning. In preliminary work on eye movements and dynamic visual acuity it was observed that the surface on which the visual targets were presented needed to be uniform, and that imperfections (e.g., wall seams, edges, specks) could interfere with an entrained eye movement tracking a target. Therefore, we elected to use as a projection surface white Lucite, which had been bent into an arc, around the object. 2.1.2. Projectors A rotating mirror (operator adjustable from 10 to 150 degrees per second (dps)) and a slide projector (KODAK 4400 Carousel) were mounted on platforms attached to the structure above the participant’s head. The laser projector (5 mW) employed was between 633 and 670 nm in wavelength (RED) and was positioned at the same distance from the screen as the slide projector and installed at an angle of 180 from the rotating mirror. The projectors were both aligned at opposing positions in order to permit test administrators to alternate use of the projectors (laser and slide) without removing one and installing the other. 2.1.3. Stimuli The Landolt C’s used with the traditional device were produced using a single black form that was designed using AutoCad. This form was then photographed at three viewing distances using Kodak Professional 100 ASA Black & White film in order to produce negatives. These negatives were mounted in slide holders which when viewed from the chin rest subtended 2.14, 1.67 and 1.26 of retinal angle respectively. At this distance (1.5 m), the gap sizes were 0.62, 0.38 and 0.24 , respectively, narrower than typical Landolt C’s (Graham, 1965; p. 324) but when tested empirically they were effective. All Landolt slides were photographed with the gap in the 45 orientation and these were positioned in the projector for presentation to the participant at either 45, 135, 225 or 315 , respectively. Viewed against the background of the whiteboard (2.4 f.c), the contrast ratios of the Landolt C’s were þ10.4, þ6.2 and þ3.2% for the three targets, respectively. The laser targets were presented in the form of M, N, V and W’s. The size of each of the three laser targets in retinal angle subtense was the same as the Landolt C’s but their contrast ratios were higher; being approximately 14% for the three sizes. The original plan had been to employ Landolt C’s drawn by laser, but that particular laser object had a 5 msec drawing time and it turned out that for moderate and fast moving objects it produced a form of visual distortion in the Landolt C’s. In future work it will be necessary to use a narrower aperture in the laser beam and an acousto-optic shutter to control for this problem. In any case, letters were used because they were controllable, although it is recognized that letter recognition may not be the same as gap detection (cf., Riggs, 1965). Incidentally, laser targets were used because digital images such as those projected with refresh rates up to 60 Hz can be detected as broken up when the eye and subject are vibrated (Riley, 1977). The temporal resolution of the visual system for moving targets of high contrast can be up to 100 Hz (Bridgeman, 1995), and in preliminary
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studies it was discovered that a projected optotype such as a Landolt C needed to be drawn in less than 3 ms to remain uniform, and so special galvanometers, driving laser images, were used as targets.
2.2. Procedure Each participant visited the laboratory on two occasions on different days. When each participant arrived they were given the Snellen wall chart test and the Dvorine color blindness test. Each participant was then given a DVA test with the slide projector, a visual span test, and the DVA test with the laser. 2.2.1. Slide task The turntable was set to one of three speeds (slow, medium, or fast) during the experiment. In all cases, the slow speed was 60 dps. Half of the participants (Group 1) had their next two speeds set at 75 and 90 dps, and the other half (Group 2) had speeds of 90 and 120 dps. There were 48 presentations of slides per session because there were three sizes four orientations four replications. The four orientations correspond to where the gap in the Landolt Cs appeared. The gaps were located in the upper left, upper right, lower left, and lower right corners with equal frequency. Each group of 12 was randomized with a different key (seeded with a value from the computer’s clock), and all four groups were combined for the master order of all 48 slides. All participants were presented the images in this order for the slow and fast conditions, while the medium condition presented the slides in reverse order. In other words, presentation proceeded forward through the 48 slides (1–48), and then backward through the same slides (48–1), then forward again through the slides (1–48). Slides were presented as a group for the slow condition (speed), the medium condition, and the fast condition. Each grouping was called a block; the collection of all blocks (slow, medium, and fast) was called a session. Each participant was present for three sessions of slide scores: 1 on the first day, and 2 on the second day. As such, the first day required 1 h to complete, and the second day took 2 h to complete. Participants were read instructions and given five practice slides before beginning each day’s blocks. Each session consisted of 48 trials. Slide scores for all variables (session, speed, replication and orientation) were calculated by percent correct. Participants responded to these slides via a control box connected to the computer’s game (joystick) port (a simple 15-pin serial connection). The control box consisted of four buttons arranged to correspond to the four image orientations, and each button was labeled with an image of the appropriate stimulus. The upper left button was for upper left gaps, while the lower right button was for lower right gaps. Participants were given 1-min breaks between each trial while the experimenter adjusted the speed of the turntable, and a 5-min break after the conclusion of each block. Each block required approximately 15 min to complete. 2.2.2. Laser task The laser task involved presenting stimuli on the display screen via a small laser projector. The presentation of velocities in the laser task followed exactly what was used in the slide presentation design. The images were presented via the turntable at the same slow, medium, and fast speeds that were used in the slide presentations and the images consisted of three sessions over 2 days, with three trials (speeds) in each block. Each block also consisted of 48 images: three sizes (small, medium, and large) four letters four replications. The projected sizes of the images matched the projected sizes of the Landolt C’s exactly but the task
involved the correct recognition of letters rather than the detection of gap orientation. The letters ‘‘M’’, ‘‘N’’, ‘‘V’’, and ‘‘W’’ were specially selected because of their similarities as implemented with a laser drawing. The method used in drawing the letters was also designed to promote confusability. The letters’ vectors (component lines) were drawn at 15 off the vertical. For instance, the lines composing the ‘‘M’’ were drawn at an angle, and removing the last line from the ‘‘M’’ yielded the ‘‘N’’, and removing the first line from the ‘‘N’’ yielded the ‘‘V’’. The ‘‘W’’ was a vertically mirrored image of the ‘‘M’’. Participants saw the images and responded by saying the appropriate letter aloud. Participants were asked to say ‘‘no’’ for the ‘‘N’’ in order to avoid confusion with the ‘‘M’’. The presentation of the stimuli followed the same randomized set as the slide task, replacing ‘‘M’’ for an upper left gap, ‘‘N’’ for the upper right gap, ‘‘V’’ for the lower left gap, and ‘‘W’’ for the lower right gap. Each trial was presented in the same way as the slides were, and the laser tasks were always presented after the slide tasks. 2.3. Other measures 2.3.1. Visual span Participants were given a single task from the Temporal Factors Battery (Jones and Kennedy, 1995) called visual span. Visual span resembles most of the tasks relating to dynamic visual acuity and when the battery was originally developed (Williams et al., 1988) it was initially programmed to serve this role. In the current study the task was administered on a standard PC (Pentium 200 MMX) and displayed on a standard VGA monitor (1400 Gateway 1024NI). The task was given twice during each day: once halfway through the day’s tasks, and once more at the conclusion of each day. The task took approximately 2 min for each trial, and a description of the task follows. A square C opening to the right or opening to the left (a backward C) was presented on the left side of the screen and then on the right side. Sometimes the two Cs both faced forward, and sometimes one would face forward and the other backward. The participant’s task was to determine whether the opening of the C on the left and right sides of the screen was the same or different orientation. The participant was given 4 s to make the determination. The ‘‘best PEST’’ (parameter estimation of sequential testing) procedure (Lieberman and Pentland, 1982) was used to determine threshold velocity for making the discrimination. 2.3.2. Color blindness screening (Dvorine Plates) As previously mentioned, the Dvorine Pseudo-Isochromatic Plates (Dvorine, 1953) were used as a screening test to detect redgreen visual color deficiency (protanope and deuteranope types). This test contained one demonstration plate (the number 48 in red on a blue background) and 14 plates made up of eight different color combinations arranged in pairs of identical colors. The plates were held approximately 30 inches in front of the participant for no more than 5 s per plate. Participants were asked to verbally identify the number they saw on each plate. Incorrect responses to three or more plates indicated red-green defective vision. 2.3.3. Static visual acuity (Snellen-like) wall chart A standard high contrast wall chart was used to assess static visual acuity. For this experiment, the Ennovation ‘‘Screening Eye Chart’’ was used. Participants were instructed to start reading the letters on the chart starting at the beginning (20/400 vision) and continue until instructed to stop. Participants were stopped when
J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273
they missed two letters, claimed they could not comfortably read further, or took an excessive amount of time to read the letters (>10 seconds each). The recorded vision was the last line for which a participant correctly read all the letters.
3. Group I experiment
100
90
Percent Correct
2.3.4. Other variables These variables included self-reports of handedness, gender and age.
3.1. Participants
80
70
60
50 SlideG1
Twenty-three participants (16 females, average age ¼ 17.9; seven males, average age ¼ 18.1) were recruited from an undergraduate General Psychology class at the University of Central Florida. Participants were required to possess at least 20/40 corrected vision, and reportedly be free of known visual defects. Participants were screened for color blindness and static visual acuity and were compensated via either pay ($6/hour) or extra credit (2 points/hour), but not both. Most participants elected to receive extra credit. Almost all participants required 3 h to complete the experiment. Prior to taking part in the study, all participants were asked to complete a written informed consent form. 3.2. Procedure The procedure followed in this experiment is the same as described above. Participants in the experiment were exposed to the narrow range of velocities (60, 75 and 90 dps) and were referred to as Group I. 3.3. Results Two ANOVAs, one each for the two test modes used (‘‘slide’’ and ‘‘laser’’) by Group I, were performed on the data. The two ANOVAs exhibited very similar patterns with all main effects (i.e., sessions, speeds, sizes, replications, and orientations/letters) statistically significant (p generally < 0.000). Additionally, several of the same two-way interactions were significant in both ANOVAs. 4. Group II experiment
SlideG2
LaserG1
LaserG2
40 1
2
3
Session Fig. 1. Percent correct by session.
4.3. Results Two ANOVAs, one each for the two test modes used (‘‘slide’’ and ‘‘laser’’) by Group II, were performed on the data. The two ANOVAs exhibited very similar patterns with all main effects (i.e., sessions, speeds, sizes, replications, and orientations/letters) statistically significant (p generally < 0.000). Additionally, several of the same two-way interactions were significant in both ANOVAs. 5. Overall results of Groups I and II Because the four ANOVAs conducted on the two groups exhibited very similar patterns with all the main effects statistically significant, and because several of the same two-way interactions were also significant in all four ANOVAs, their means are presented on the same graphs. Fig. 1 shows the trend over sessions for the two groups for the two test modes (i.e., four comparisons). Both sets of ‘‘slide’’ scores (Groups I and II) improve gradually and regularly (w2%) over the three sessions. Both ‘‘laser’’ scores also improve regularly (w4%) over the three sessions. It may be seen that Group I, the group with the lower range of scores (60, 75 and 90), has higher percent correct scores than Group II, and ‘‘slide’’ scores show a higher percent correct than ‘‘laser’’. In Fig. 2, the relationship between stimulus speed (or velocity) and the participants’ performances are graphically displayed. As
4.1. Participants
100
90
Percent Correct
Twenty-five participants (10 females, average age ¼ 18.3; 15 males, average age ¼ 19) were recruited from an undergraduate General Psychology class at the University of Central Florida. Participants were required to possess at least 20/40 corrected vision, and reportedly be free of known visual defects. Participants were screened for color blindness and static visual acuity and were compensated via either pay ($6/hour) or extra credit (2 points/ hour), but not both. Most participants elected to receive extra credit. Almost all participants required 3 h to complete the experiment. Prior to taking part in the study, all participants were asked to complete a written informed consent form.
269
80
70
60
50
4.2. Procedure The procedure followed in this experiment is the same as described above. Participants in the experiment were exposed to the wide range of velocities (60, 90, and 120 dps) and were referred as Group II.
SlideG1
SlideG2
LaserG1
LaserG2
40 slow
medium
Presentation Speed Fig. 2. Percent correct by speed.
fast
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J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273
100
100
90
90
80
80
Percent Correct
Percent Correct
UL/M
70
60
50
UR/N
BL/V
BR/W
70
60
50 SlideG2
SlideG1
LaserG2
LaserG1
40
40 small
medium
large
SlideG1
Stimulus Size
SlideG2
LaserG1
LaserG2
Fig. 5. Percent correct by stimulus.
Fig. 3. Percent correct by size.
expected, within each task, the faster presentation velocities were more difficult for the participants and produced lower scores. It should be noted that both groups (I and II) and both methods (‘‘laser’’ and ‘‘slide’’) were tested at 60 dps and these show similar results (near 100% correct). Both groups (i.e., I and II) were also tested at 90 dps and differences between groups were statistically significant for ‘‘slide’’ (p < 0.02) and ‘‘laser’’ (p < 0.01) with Group I showing the better performances in both comparisons. As for target size, predictably, there is a better performance (higher percent correct) for larger targets for both tasks (‘‘slide’’ and ‘‘laser’’) for both groups (Fig. 3). While it may be seen that in Fig. 4 which represents percent correct by replication, three of the four curves show a slight tendency to decline within a session and one does not, in all cases the within session changes are <4%. We will be sensitive to task length in future work where we will attempt to study this and other procedural effects. With regard to the percent correct by stimulus, of the four orientations of the ‘‘slide’’ and the four letters of the ‘‘laser,’’ the right orientations, particularly the ‘‘45 orientation’’, appeared
100
Percent Correct
90
80
70
most difficult on the slide task. The laser task revealed that the ‘‘W’’ turned out to be the most difficult letter to identify, closely followed by the ‘‘V’’ (Fig. 5). 5.1. Within task correlations 5.1.1. Correlations of individual sessions Tables 1 and 2 show the within test (retest) correlations for the three sessions for the two groups. In all four matrices, the within test (retest reliability) correlations were significantly different from zero (p < 0.05), and, on the average, the highest retest correlations are found for laser/Group II and the lowest ones for slide/Group I. 5.1.2. Aggregation of data One of the ways to evaluate comparability between the two tests was to aggregate the scores and correlate them. Prior to combining these data, Lawley’s test for the equality of all retest correlations (Morrison, 1967) was applied and it was found that none of the intra-session correlations in the four retest correlation matrices showed evidence of significance (p > 0.10). This lack of significance of the cross-session correlations implies differential stability (Jones, 1980; Steiger, 1980), particularly when standard deviations over sessions are constant, as they were in this experiment. Furthermore, the means over sessions were monotonic (cf., Fig. 3), which appears to be a practice effect and may imply learning. But the improvement over sessions was small (w3%), well behaved, and it is arguable that the improvements did not appear to reflect differences in learning rate, although this question remains to be answered in future work. In any case, we considered that what we would gain in simplicity by aggregation of all the ‘‘slide’’ and ‘‘laser’’ data for each of the two groups would be of use in the comparison of the two tests as well as when comparing correlations between both sets of DVA scores and other variables.
60 Table 1 Correlations: slide and laser, Group I (60, 75, 90).
50 SlideG1
SlideG2
LaserG2
LaserG1
40 1
2
3
Replication Fig. 4. Percent correct by replication.
4
Correlations
Slide 1
Slide 2
Slide 3
Laser 1
Laser 2
Laser 3
Slide 1 Slide 2 Slide 3 Laser 1 Laser 2 Laser 3
1.0000 0.6582 0.4999 0.8070 0.5422 0.4663
0.6582 1.0000 0.7006 0.6504 0.6899 0.5054
0.4999 0.7006 1.0000 0.5653 0.6326 0.7245
0.8070 0.6504 0.5653 1.0000 0.7833 0.6339
0.5422 0.6899 0.6326 0.7833 1.0000 0.7789
0.4663 0.5054 0.7245 0.6339 0.7789 1.0000
J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273 Table 2 Correlations: slide and laser, Group II (60, 90, 120).
Table 4 Correlations: DVA with other variables, Group I (60, 75, 90).
Correlations
Slide 1
Slide 2
Slide 3
Laser 1
Laser 2
Laser 3
Slide 1 Slide 2 Slide 3 Laser 1 Laser 2 Laser 3
1.0000 0.9008 0.7762 0.7222 0.6478 0.5459
0.9008 1.0000 0.8112 0.7935 0.7465 0.5991
0.7762 0.8112 1.0000 0.6901 0.6310 0.5034
0.7222 0.7935 0.6901 1.0000 0.8918 0.7770
0.6478 0.7465 0.6310 0.8918 1.0000 0.8781
0.5459 0.5991 0.5034 0.7770 0.8781 1.0000
Key: r ¼ 0.39 (p ¼ 0.05); r ¼ 0.52 (p ¼ 0.01); r ¼ 0.66 (p ¼ 0.001).
Correlations Handedness Gender Age SLIDE LASER
0.2462 0.2659
5.2.2. Averaging correlations Another way to examine the relationship between performances on the two tasks is to average correlations (Dunlap et al., 1986; Bittner et al., 1982) rather than correlating averages, as what was done above with aggregation of the three sessions of data. In addition to the retest correlations, Table 1 (Group I) and Table 2 (Group II) also show the between test (cross-task) correlations of ‘‘laser’’ and ‘‘slide’’. It may be seen that all nine cross-task correlations in each table are statistically significant (p < 0.05). The retest correlations of Tables 1 and 2 were then averaged separately for ‘‘laser’’ and ‘‘slide’’ and for the two Groups and then entered into the diagonal of Table 3. Then the nine between task correlations were likewise averaged and entered into the superdiagonal of Table 3. Finally the correction for attenuation formula (Spearman, 1904):
r12 R12 ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi r11 r22
(1)
was used to correct for reliability attenuation of the measures (cf., also Gulliksen, 1987). In the diagonal, in parentheses, are the average retest reliability for the two groups for the ‘‘laser’’ and ‘‘slide’’. Above the diagonal is the average cross-task correlation between ‘‘laser’’ and ‘‘slide’’ for each group and below the diagonal is the corrected for attenuation correlation. It may be seen that ‘‘laser’’/’’slide’’ comparisons, corrected for attenuation, are R ¼ 0.92 for Group I and R ¼ 0.78 for Group II, which signify a close correspondence between the two tests and imply that ‘‘laser’’ could be used instead of the traditional slides with minimal loss in validity. 5.3. Other findings Tables 4 and 5 show correlations between the aggregated DVA measures and the other variables. While in both groups ‘‘laser’’ and ‘‘slide’’ are correlated with each other, neither measure, in either group, is related to gender or handedness. Visual span, the test most obviously like DVA, correlated with ‘‘slide’’ and ‘‘laser’’ for Table 3 Correlations: correction for attenuation.
Slide Laser
Group II
Color blindness
Static visual
0.2083 0.1413
0.1842 0.1463
Table 5 Correlations: DVA with other variables, Group II (60, 90, 120). Correlations Handedness Gender Age
5.2.1. Aggregation of data All the data for three sessions, three velocities, three sizes, four replications, and four orientations, were summed for each participant for the two tasks independently (‘‘laser’’ and ‘‘slide’’) and these data were correlated over all the participants separately for Group I and for Group 2. These two correlations between ‘‘laser’’ and ‘‘slide’’ were r ¼ 0.54 and r ¼ 0.70 for Groups I and II, respectively.
Visual span
0.1138 0.0395 0.1415 0.3769 0.0222 0.0664
5.2. Between task correlations
Group I
271
SLIDE LASER
0.3008 0.0396
Visual span
0.0197 0.1103 0.4535 0.2632 0.1934 0.3833
Color blindness
Static visual
0.2297 0.2604
0.1615 0.0443
Key: r ¼ 0.39 (p ¼ 0.05); r ¼ 0.52 (p ¼ 0.01); r ¼ 0.66 (p ¼ 0.001).
Group II (p < 0.05), but did not relate to either task for Group I. Relatedly, static (i.e., Snellen) acuity and color vision scores were zero in all four DVA comparisons. 6. Discussion and conclusions The primary objective of this project was the development of a reasonably priced, highly flexible, portable, valid and reliable instrument for the assessment of DVA. The major question asked was whether implementation of targets via laser would be able to provide comparable data to the more traditional Landolt C presentation. To answer this empirical question a device patterned after the Ludvigh and Miller (1953) and Long and Penn (1987) devices was assembled. Then, using slightly different velocity parameters, two formal studies were conducted with both devices employing about 25 participants for each. When the two tests in the two groups were compared, using two analytic approaches, strong and significant correlations between the two tasks were found. If the scores from the traditional device can be considered the standard, it appears that the measures from the laser system may be considered comparable for the comparisons made. This implies that development of a portable, flexible device is feasible. While letter targets were employed in this work, the laser offers the opportunity to experiment with many other forms, luminance, contrasts, sizes, etc. In the future, the plan is to explore much of this experimental ‘‘space’’ in psychophysical studies. As further evidence of the comparability of the two DVA test methods, it also appears that essentially the same main effects were significant in both devices and performances were similar over the two devices and in both groups. Although the sample sizes were small, the data sets were largely regular and the two groups provided a form of cross validation for each other since stimulus characteristics appeared to be more of a factor than ‘‘laser’’ versus ‘‘slide’’ presentation. Thus there were some inferences that could be made from the data as collected. First, and not surprisingly, the letter recognition task may have been more difficult than the orientation detection task, and thereby partly explains the differences in performance where for the same velocities ‘‘slide’’ scores were better than ‘‘laser’’ scores. Next, there appeared to be a context effect, whereby there were small differences between the performances of the two groups at their respective 90 dps condition, with the group having the higher range of scores doing less well than did the group with the lower range of velocities. 6.1. Additional factors
Slide
Laser
Slide
Laser
(0.6196) 0.9212
0.5373 (0.7320)
(0.8294) 0.7785
0.6973 (0.8490)
There is other work still to be carried out in order to produce an alternative to the ‘‘slide’’ method of DVA testing. For example,
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researchers could improve on the metric properties (reliability, stability) of the laser device and they could also generalize these findings from the narrow range of stimulus characteristics used in this study (velocities, shapes, sizes, contrasts, brightness, etc.). Furthermore, they could also examine time course changes which may result from fatigue and tedium of too long sessions. Additional findings to be explored further include what appeared to be a practice or learning effect over the three sessions. This result is consistent with what others have reported in the literature (e.g., Ludvigh and Miller, 1954, 1955) and should be further explored. If DVA performance can be improved by practice, and if DVA is indeed involved in the performance of various tasks like driving, perhaps training can be employed for persons who may have lost some function through injury or aging. Additional stimulus factors that might prove to be of interest are the type of stimulus motion (linear versus accelerative) and the form of the target (Vernier targets, other objects, etc.). Furthermore, test administrators must be able to adjust or program the dependent measure (e.g., target size) in a psychometrically sound manner that permits the rapid determination of a naive observer’s score (e.g., threshold size) for a given set of conditions. Other stimulus variables include target (i.e., screen) distance and background characteristics and being able to change the target shape after the eye is entrained and is tracking the target (i.e., within 5 msec). Additionally, the laser would permit the generation of new and more realistic tasks that would also measure dynamic visual acuity. These tasks could be presented on a personal-computer setup. It would also be useful to establish how DVA is distributed in the population or whether like visual acuity, it might be that most people have an equivalent amount unless there was damage to the system. Although the homogeneity of this group could be expected to cause the range of scores to be restricted, correlations were still obtained between DVA measured via both ‘‘slide’’ and ‘‘laser’’ methods. Doubtless this range restriction also influenced correlations with other variables and a broader attempt should be made in future work to examine how several visual and cognitive tests correlate. This research seems to indicate that both DVA tests correlate with each other, but not with three other visual tests. This lends support to the contention (Kandel et al., 1995) of a separate smooth pursuit system. At the same time, individual differences in DVA ability, even in a homogeneous population, are fairly large, and thus DVA appears to be a useful target for further study.
6.2. Advantages of laser DVA devices Laser has several advantages over the traditional device since the laser does not work from fixed pictures which need to be photographed in advance and may entail increased experimental time to run because of slowness of presentations. The chief advantage of the laser system is that it is flexible, and images can be modified and scaled easily and so different forms and shapes may be used. In a laser system one can vary presentation speed easily and accurately, presentations of the stimulus can be tracked easily and there is a minimum of moving parts. Other advantages include the fact that a laser can project over a large area, thereby allowing for large stimuli that traverse a larger visual angle. Next, virtually any type of dotted or lined stimuli can be projected (e.g., simple spot, vertical or horizontal lines, boxes, cars, etc.). Laser also has far greater flexibility in display of dynamic stimuli. Rather than displaying only horizontal translation, it is capable of displaying stimuli that change size and translate at the same time. Therefore, the stimulus can change its acuity demand after the eye is entrained in motion. This latter issue has always been a problem
with the more conventional device and study of the implications can refine what we know about DVA. 6.3. Future research A DVA test, perhaps as part of a battery of visual tests, seems to be a useful addition to the array of existing measures used in driver research and education. Also, if supported in a larger study, these findings are an extremely important step in establishing the hypothesized link between this visual ability and automobile crashes, especially as older drivers are concerned. Aging and driving crashes are related to DVA scores. Together, the results suggest a model of age effects on visual and cognitive abilities and associated components of driving which can be used to guide future research in this area. Our future research plans include: (1) conducting a replication of the psychometrics of this study but broadening the stimuli presented and creating normative data with a larger number of participants; using a large number of visual targets; (2) determining whether a sample of participants have relationships between DVA thresholds and automobile crash history; (3) examining the effects of age and blood alcohol on DVA with self-reports of crashes; and (4) extending the predictive validities to job performance on a high fidelity simulator. 6.4. Conclusions The goal of this research was to develop a valid and reliable portable DVA system using a low-energy laser. The laser device developed was compared to a traditional DVA device in two withinsubjects, repeated measures designs. The findings of these studies indicated that: (1) retest reliabilities of the two DVA devices were comparable and higher with the laser; (2) average correlations between the two devices were r ¼ 0.62 (p < 0.01) and r ¼ 0.65 (p < 0.01) for the two devices respectively; and (3) after correction for reliability attenuation these correlations improved to r ¼ 0.92 and r ¼ 0.78. These findings indicate that a flexible and portable DVA laser device can be developed to measure the same construct as the more traditional bulky DVA device. As such, this device could be used to assess individual DVA more easily and to serve as a predictor of visual requirements in many real-world settings, especially driving. References Bittner Jr., A.C., Dunlap, W.P., Jones, M.B., 1982. Averaged cross-correlations with differentially-stable variables: fewer participants required with repeated measures. Proceedings of the Human Factors Society 26 (5), 349–353. Bridgeman, B., 1995. Direction constancy in rapidly refreshed video displays. Journal of Vestibular Research 5 (6), 393–398. Burg, A., 1966. Visual acuity as measured by dynamic and static tests: a comparative evaluation. Journal of Applied Psychology 50, 460–466. Burg, A., 1967. The Relationship Between Vision Test Scores and Driving Record: General Findings. (Report No. 67-24). University of California, Department of Engineering, Los Angeles, CA. Burg, A., 1968. Vision Test Scores and Driving Record: Additional Findings. (Report No. 68-27). University of California, Department of Engineering, Los Angeles, CA. Burg, A., 1971. Vision and driving: a report on research. Human Factors 13, 79–87. Committee on Vision of the National Research Council (U.S.), 1985. Emergent Techniques for the Assessment of Visual Performance. National Academy Press, Washington, DC. DeKlerk, L.F.W., Ernst, J.Th., Hoogerheide, J., 1964. The dynamic visual acuity of 30 selected pilots. Aeromedica Acta 9, 129–136. Dunlap, W.P., Silver, N.C., Bittner, A.C., 1986. Estimating reliability with small samples: increased precision with averaged correlations. Human Factors 28 (6), 685–690. Dvorine, E., 1953. Dvorine Pseudo-Isochromatic Plates. Harcourt, second ed. Brace & World, Inc., New York. Farrimond, T., 1967. Visual and auditory performance variations with age: some implications. Australian Journal of Psychology 19, 193–201. Graham, C.H. (Ed.), 1965. Vision and Visual Perception. John Wiley & Sons, Inc, New York. Gulliksen, H., 1987. Theory of Mental Tests. Lawrence-Erlbaum Associates, Hillsdale, NJ.
J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273 Henderson, R.L., Burg, A., 1973. The Role of Vision and Audition in Truck and Bus Driving (Tech. Rep. TM-(L)-5260/000/00). Systems Development Corp, Santa Monica, CA. Hoffman, L.G., Rouse, M., Ryan, J.B., 1981. Dynamic visual acuity: a review. Journal of the American Optometric Association 52, 883–887. Ishigaki, H., Miyao, M., 1994. Implications for dynamic visual acuity with changes in age and sex. Perceptual and Motor Skills 78, 363–369. Ishihara, K., Ishihara, S., Nagamachi, M., Osaki, H., Hiramatsu, S., 2004. Independence of older adults in performing instrumental activities of daily living (IADLs) and relation of this performance to visual abilities. Theoretical Issues in Ergonomic Science 5 (3), 198–213. Jones, M.B., 1980. Stabilization and Task Definition in a Performance Test Battery. Monograph No. NBDL-M001, Contract No. N0023-79-M-5089. Naval Biodynamics Laboratory, New Orleans [NTIS No. AD A099987]. Jones, M.B., Kennedy, R.S., 1995. Temporal factors in visual perception: a differential approach. Perceptual and Motor Skills 81, 859–867. Kandel, E.R., Schwartz, J.H., Jessell, T.M. (Eds.), 1995. Principles of Neural Science, third ed. Appleton & Lange, Norwalk, CT. Kennedy, R.S., Ordy, J.M., Dunlap, W.P., 1996. Age effects on six temporal factors in visual perception. Society for Neuroscience Abstracts 22, 183. Lieberman, H.R., Pentland, A.P., 1982. Microcomputer-based estimation of psychophysical thresholds: the best PEST. Behavior Research Methods and Instrumentation 14, 21–25. Long, G.M., Crambert, R.F., 1990. The nature and basis of age-related changes in dynamic visual acuity. Psychology and Aging 5, 138–143. Long, G.M., May, P.A., 1992. Dynamic visual acuity and contrast sensitivity for static and flickered gratings in a college sample. Optometry and Vision Science 69, 915–922. Long, G.M., Penn, D.L., 1987. Dynamic visual acuity: normative functions and practical implications. Bulletin of the Psychonomic Society 25, 253–256. Ludvigh, E., Miller, J.W., 1953. A Study of Dynamic Visual Acuity (Research Report No. NM 001 067.01.01). U.S. Naval School of Aviation Medicine, Pensacola, FL. Ludvigh, E., Miller, J.W., 1954. Some Effects of Training on Dynamic Visual Acuity (Research Report No. NM 001 075.01.06). U.S. Naval School of Aviation Medicine, Pensacola, FL.
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Ludvigh, E., Miller, J.W., 1955. The Effects on Dynamic Visual Acuity of Practice at One Angular Velocity on the Subsequent Performance at a Second Angular Velocity (Research Report No. NM 001 110 501.09). U.S. Naval School of Aviation Medicine, Pensacola, FL. Miller, J.W., Ludvigh, E.J., 1962. The effect of relative motion on visual acuity. Survey of Ophthalmology 7, 83–116. Morrison, D.F., 1967. Multivariate Statistical Methods. McGraw Hill, New York. Morrison, T.R., 1980. A Review of Dynamic Visual Acuity (NAMRL Monograph No. 28). Naval Aerospace Medical Research Laboratory, Pensacola, FL. Reading, V.M., 1972a. Analysis of eye movement responses and dynamic visual acuity. Pflugers Archives 333, 27–34. Reading, V.M., 1972b. Visual resolution as measured by dynamic and static tests. Pflugers Archives 333, 17–26. Riggs, L.A., 1965. Visual acuity. In: Graham, C.H. (Ed.), Vision and Visual Perception. John Wiley & Sons, Inc., New York, pp. 321–349. Riley, T.M., 1977. Multiple images as a function of LEDs viewed during vibration. Human Factors 19 (1), 79–82. Schma¨l, F., Thiede, O., Stoll, W., 2003. Effect of ethanol on visual-vestibular intersections during vertical linear body acceleration. Alcoholism: Clinical and Experimental Research 27 (9), 1520–1526. Sharpe, J.A., Sylvester, T.O., 1978. Effects of aging on horizontal smooth pursuit. Investigative Ophthalmology and Visual Science 17, 465–468. Shinar, D., 1977. Driver Visual Limitations Diagnosis an Treatment. Final Report No. DOT HS 803 260, Contract No. DOT-HS-5-01275. U.S. Department of Transportation, Washington, DC. Spearman, C., 1904. The proof and measurement of association between two things. American Journal of Psychology 15, 72–101. Spooner, J.W., Sakala, S.M., Baloh, R.W., 1980. Effect of aging on eye tracking. Archives of Neurology 37, 575–576. Steiger, J.H., 1980. Tests for comparing elements of a correlation matrix. Psychological Bulletin 87, 245–251. Williams, M., Kennedy, R.S., Baltzley, D.R., May, J.G., Dunlap, W.P., 1988. Reliability, Stability, and Cross-task Correlations of Six Visual Temporal Factor Tests. Essex Corporation. Essex Orlando Technical Report, Orlando, FL.
Contents lists available at ScienceDirect
Applied Ergonomics journal homepage: www.elsevier.com/locate/apergo
A portable device for the assessment of dynamic visual acuity Janan Al-Awar Smither a, *, Robert S. Kennedy b a b
Department of Psychology, University of Central Florida, Orlando, FL 32816-1390, USA RSK Assessments, Inc., Orlando, FL, USA
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 January 2008 Accepted 24 July 2009
Dynamic visual acuity (DVA) thresholds are among the few visual functions predictive of automobile crashes. DVA is also sensitive to alcohol and aging. However, measuring DVA is awkward because there is no standardized, efficient, flexible apparatus for DVA assessment. In this project, we developed a prototype of an automated, portable DVA system using a low-energy laser, and we compared this laser DVA with the traditional device in two within-subjects, repeated measures designs. The two studies included 48 participants (22 males and 26 females with an average age of 18.33 years). The most important findings were that: (1) retest reliabilities of the two DVA devices were comparable and higher with the laser; (2) average correlations between the two devices were r ¼ 0.62 (p < 0.01) and r ¼ 0.65 (p < 0.01) for the two designs respectively; and (3) after correction for reliability attenuation these improved to r ¼ 0.92 and r ¼ 0.78. These findings indicate that a flexible DVA laser device can be developed to measure the same construct as the more traditional bulky DVA device. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: Dynamic visual acuity Visual screening Portable DVA
1. Introduction Dynamic visual acuity (DVA) has had an impressive research history which suggests that it represents a possible visual functioning screening and classification system largely untapped by the military and private sectors. A common complaint raised repeatedly throughout the 50-year history of DVA research has been the concern that there is no standardized, efficient, flexible apparatus for DVA assessment. In our effort we sought to determine the feasibility of designing such an apparatus by showing comparability with a standard test. We also assessed the feasibility of using laser and computer technology to implement menu-driven production of targets and prototypes of specified sizes, velocities, optotypes, and motion-types in a manner that may be readily tailored to a researcher’s needs, or to the particular demands of a clinical or vocational setting in which the instrument is used. 1.1. General history of DVA The empirical history of DVA is usually traced to the work of Ludvigh at the end of WWII (see Miller and Ludvigh, 1962; Morrison, 1980; Hoffman et al., 1981). Ludvigh first reported the dramatic fall-off in acuity as target velocity was increased to even modest levels and he described this relationship with a simple exponential * Corresponding author. Tel.: þ1 407 823 5859; fax: þ1 407 823 5862. E-mail address: [email protected] (J. Al-Awar Smither). 0003-6870/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.apergo.2009.07.008
function, y ¼ a þ bx3 (where y is threshold target size, a and b are empirically-determined parameters, and x is target velocity). Since Ludvigh’s early work, two factors have provided the continued interest in DVA. First, DVA is not predictable solely from static acuity. There is only a modest correlation between static acuity and DVA, and even this tends to disappear as target velocity exceeds approximately 60 /s (Morrison, 1980). This suggests DVA, which requires precise oculomotor functioning in addition to optical and neural resolution, is not revealed by a determination of traditional acuity alone. More recently, research has shown that DVA is also unrelated to observers’ contrast sensitivity (Long and May, 1992). Second, DVA appears to be related to many real-world activities more strongly than is static acuity. As the Committee on Vision of the National Research Council (1985) has reviewed, higher DVA performance in the laboratory has been associated with both lower driving crash rates (Burg, 1967, 1968, 1971; Henderson and Burg, 1973; Shinar, 1977) and certain in-flight performance measures for pilots (DeKlerk et al., 1964). It is critical to note that these relationships exist among individuals who have been prescreened for good static acuity (minimum 20/25). 1.2. Relationship between DVA, alcohol, and aging DVA can be conceptualized as a global or composite measure of oculomotor visual functioning (Committee on Vision of the National Research Council, 1985; Morrison, 1980; Hoffman et al., 1981). DVA is presumed to reflect the integrated functioning of
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optical, sensory, and motor components of the visual system and it is clearly required for many real-world activities in a dynamic setting. DVA is more likely a factor in the reduced performance related to alcohol or aging effects than is traditional static visual acuity. Schma¨l et al., (2003) found that alcohol significantly increased latency no matter the subjects’ levels of alcohol consumption. Ishihara et al. (2004) found similar decrements in elderly individuals. The relative contributions of the underlying components (e.g., saccadic latency, saccadic accuracy, saccadic frequency, pursuit accuracy, optical clarity, neural channel sensitivity, etc.) need not be formally specified for the global DVA measure to prove useful for the evaluation of alcohol or aging effects applied to contexts such as driving. The practical difficulties of assessing many of these factors separately in an applied context are effectively avoided. The relevance of alcohol’s effects on DVA for the proposed research program can be summarized succinctly: (a) an individual’s DVA cannot be predicted from the assessment of his/her static acuity; (b) DVA has been reported to be significantly correlated with driving performance (and other applied tasks); and (c) even low-moderate levels of alcohol can degrade DVA. Although a 20/40 criterion may be adequate to obtain a driver’s license, individuals may differ markedly in their visual capacity to resolve or discriminate objects once they are in motion. This clearly suggests that current static vision tests for licensing drivers are incomplete, particularly in terms of testing drug/alcohol users, the elderly, and individuals with a variety of ocular problems and pathologies. Development of a valid and reliable DVA test would represent a major contribution as an ‘‘emerging technology’’ for more accurate and reliable assessment of critical dynamic visual acuity functions to serve as a predictor of visual requirements in many real-world settings, particularly driving. There is a little question concerning age and its effects on DVA. Several studies have demonstrated severe degradation in DVA performance with increasing age after about the fourth decade. Burg’s famous DVA work (1966) with a sample size of 17,500 participants ranging in age from 16 to 92 years has provided a powerful picture of an age-dependent decline in visual performance. Subsequent DVA studies have reaffirmed these results under differing conditions and procedures (e.g., Farrimond, 1967; Ishigaki and Miyao, 1994; Long and Crambert, 1990; Reading, 1972a, b). Very importantly, it should be noted that this age-dependent decline in DVA performance is evident even when the elderly participants are prescreened for minimum static acuity levels of 20/40. Clearly, the drop-off in DVA performance with advancing age is not dependent or predictable from changes in static acuity levels alone. Moreover, these results are consistent with reports of an age-dependent decline in eye movement efficiency revealed from direct eye movement recording (e.g., Sharpe and Sylvester, 1978; Spooner et al., 1980). Recently, Kennedy et al. (1996) showed age-related performance in saccadic accuracy and other temporal factors tests in a small (N ¼ 25) group of participants aged 35–75. Given the important role DVA can play in the performance of real-world tasks, and the fact that currently there is no standardized, efficient, and flexible apparatus for DVA assessment, the aim of this research was to develop a reliable, automated and portable DVA device to serve as a predictor of visual requirements in many real-world settings, particularly driving. 2. Method 2.1. Apparatus The first objective was to construct a DVA device that would be portable and easy to use. This device also needed to compare
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favorably with the traditional DVA device. The plan was to assemble a facsimile of the original device, then conduct repeated measures, within-subjects empirical tests with the new and old devices, and then compare whether the two apparatuses measured the same visual process and, if so, how well the new device measured DVA. 2.1.1. Projection screen A screen was constructed using a highly reflective (>80%) flexible whiteboard material which provided an effective viewing area of 46.6 to either side of center for a total view angle of 93.2 forward as situated from the chin rest which ensured proper head positioning. In preliminary work on eye movements and dynamic visual acuity it was observed that the surface on which the visual targets were presented needed to be uniform, and that imperfections (e.g., wall seams, edges, specks) could interfere with an entrained eye movement tracking a target. Therefore, we elected to use as a projection surface white Lucite, which had been bent into an arc, around the object. 2.1.2. Projectors A rotating mirror (operator adjustable from 10 to 150 degrees per second (dps)) and a slide projector (KODAK 4400 Carousel) were mounted on platforms attached to the structure above the participant’s head. The laser projector (5 mW) employed was between 633 and 670 nm in wavelength (RED) and was positioned at the same distance from the screen as the slide projector and installed at an angle of 180 from the rotating mirror. The projectors were both aligned at opposing positions in order to permit test administrators to alternate use of the projectors (laser and slide) without removing one and installing the other. 2.1.3. Stimuli The Landolt C’s used with the traditional device were produced using a single black form that was designed using AutoCad. This form was then photographed at three viewing distances using Kodak Professional 100 ASA Black & White film in order to produce negatives. These negatives were mounted in slide holders which when viewed from the chin rest subtended 2.14, 1.67 and 1.26 of retinal angle respectively. At this distance (1.5 m), the gap sizes were 0.62, 0.38 and 0.24 , respectively, narrower than typical Landolt C’s (Graham, 1965; p. 324) but when tested empirically they were effective. All Landolt slides were photographed with the gap in the 45 orientation and these were positioned in the projector for presentation to the participant at either 45, 135, 225 or 315 , respectively. Viewed against the background of the whiteboard (2.4 f.c), the contrast ratios of the Landolt C’s were þ10.4, þ6.2 and þ3.2% for the three targets, respectively. The laser targets were presented in the form of M, N, V and W’s. The size of each of the three laser targets in retinal angle subtense was the same as the Landolt C’s but their contrast ratios were higher; being approximately 14% for the three sizes. The original plan had been to employ Landolt C’s drawn by laser, but that particular laser object had a 5 msec drawing time and it turned out that for moderate and fast moving objects it produced a form of visual distortion in the Landolt C’s. In future work it will be necessary to use a narrower aperture in the laser beam and an acousto-optic shutter to control for this problem. In any case, letters were used because they were controllable, although it is recognized that letter recognition may not be the same as gap detection (cf., Riggs, 1965). Incidentally, laser targets were used because digital images such as those projected with refresh rates up to 60 Hz can be detected as broken up when the eye and subject are vibrated (Riley, 1977). The temporal resolution of the visual system for moving targets of high contrast can be up to 100 Hz (Bridgeman, 1995), and in preliminary
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studies it was discovered that a projected optotype such as a Landolt C needed to be drawn in less than 3 ms to remain uniform, and so special galvanometers, driving laser images, were used as targets.
2.2. Procedure Each participant visited the laboratory on two occasions on different days. When each participant arrived they were given the Snellen wall chart test and the Dvorine color blindness test. Each participant was then given a DVA test with the slide projector, a visual span test, and the DVA test with the laser. 2.2.1. Slide task The turntable was set to one of three speeds (slow, medium, or fast) during the experiment. In all cases, the slow speed was 60 dps. Half of the participants (Group 1) had their next two speeds set at 75 and 90 dps, and the other half (Group 2) had speeds of 90 and 120 dps. There were 48 presentations of slides per session because there were three sizes four orientations four replications. The four orientations correspond to where the gap in the Landolt Cs appeared. The gaps were located in the upper left, upper right, lower left, and lower right corners with equal frequency. Each group of 12 was randomized with a different key (seeded with a value from the computer’s clock), and all four groups were combined for the master order of all 48 slides. All participants were presented the images in this order for the slow and fast conditions, while the medium condition presented the slides in reverse order. In other words, presentation proceeded forward through the 48 slides (1–48), and then backward through the same slides (48–1), then forward again through the slides (1–48). Slides were presented as a group for the slow condition (speed), the medium condition, and the fast condition. Each grouping was called a block; the collection of all blocks (slow, medium, and fast) was called a session. Each participant was present for three sessions of slide scores: 1 on the first day, and 2 on the second day. As such, the first day required 1 h to complete, and the second day took 2 h to complete. Participants were read instructions and given five practice slides before beginning each day’s blocks. Each session consisted of 48 trials. Slide scores for all variables (session, speed, replication and orientation) were calculated by percent correct. Participants responded to these slides via a control box connected to the computer’s game (joystick) port (a simple 15-pin serial connection). The control box consisted of four buttons arranged to correspond to the four image orientations, and each button was labeled with an image of the appropriate stimulus. The upper left button was for upper left gaps, while the lower right button was for lower right gaps. Participants were given 1-min breaks between each trial while the experimenter adjusted the speed of the turntable, and a 5-min break after the conclusion of each block. Each block required approximately 15 min to complete. 2.2.2. Laser task The laser task involved presenting stimuli on the display screen via a small laser projector. The presentation of velocities in the laser task followed exactly what was used in the slide presentation design. The images were presented via the turntable at the same slow, medium, and fast speeds that were used in the slide presentations and the images consisted of three sessions over 2 days, with three trials (speeds) in each block. Each block also consisted of 48 images: three sizes (small, medium, and large) four letters four replications. The projected sizes of the images matched the projected sizes of the Landolt C’s exactly but the task
involved the correct recognition of letters rather than the detection of gap orientation. The letters ‘‘M’’, ‘‘N’’, ‘‘V’’, and ‘‘W’’ were specially selected because of their similarities as implemented with a laser drawing. The method used in drawing the letters was also designed to promote confusability. The letters’ vectors (component lines) were drawn at 15 off the vertical. For instance, the lines composing the ‘‘M’’ were drawn at an angle, and removing the last line from the ‘‘M’’ yielded the ‘‘N’’, and removing the first line from the ‘‘N’’ yielded the ‘‘V’’. The ‘‘W’’ was a vertically mirrored image of the ‘‘M’’. Participants saw the images and responded by saying the appropriate letter aloud. Participants were asked to say ‘‘no’’ for the ‘‘N’’ in order to avoid confusion with the ‘‘M’’. The presentation of the stimuli followed the same randomized set as the slide task, replacing ‘‘M’’ for an upper left gap, ‘‘N’’ for the upper right gap, ‘‘V’’ for the lower left gap, and ‘‘W’’ for the lower right gap. Each trial was presented in the same way as the slides were, and the laser tasks were always presented after the slide tasks. 2.3. Other measures 2.3.1. Visual span Participants were given a single task from the Temporal Factors Battery (Jones and Kennedy, 1995) called visual span. Visual span resembles most of the tasks relating to dynamic visual acuity and when the battery was originally developed (Williams et al., 1988) it was initially programmed to serve this role. In the current study the task was administered on a standard PC (Pentium 200 MMX) and displayed on a standard VGA monitor (1400 Gateway 1024NI). The task was given twice during each day: once halfway through the day’s tasks, and once more at the conclusion of each day. The task took approximately 2 min for each trial, and a description of the task follows. A square C opening to the right or opening to the left (a backward C) was presented on the left side of the screen and then on the right side. Sometimes the two Cs both faced forward, and sometimes one would face forward and the other backward. The participant’s task was to determine whether the opening of the C on the left and right sides of the screen was the same or different orientation. The participant was given 4 s to make the determination. The ‘‘best PEST’’ (parameter estimation of sequential testing) procedure (Lieberman and Pentland, 1982) was used to determine threshold velocity for making the discrimination. 2.3.2. Color blindness screening (Dvorine Plates) As previously mentioned, the Dvorine Pseudo-Isochromatic Plates (Dvorine, 1953) were used as a screening test to detect redgreen visual color deficiency (protanope and deuteranope types). This test contained one demonstration plate (the number 48 in red on a blue background) and 14 plates made up of eight different color combinations arranged in pairs of identical colors. The plates were held approximately 30 inches in front of the participant for no more than 5 s per plate. Participants were asked to verbally identify the number they saw on each plate. Incorrect responses to three or more plates indicated red-green defective vision. 2.3.3. Static visual acuity (Snellen-like) wall chart A standard high contrast wall chart was used to assess static visual acuity. For this experiment, the Ennovation ‘‘Screening Eye Chart’’ was used. Participants were instructed to start reading the letters on the chart starting at the beginning (20/400 vision) and continue until instructed to stop. Participants were stopped when
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they missed two letters, claimed they could not comfortably read further, or took an excessive amount of time to read the letters (>10 seconds each). The recorded vision was the last line for which a participant correctly read all the letters.
3. Group I experiment
100
90
Percent Correct
2.3.4. Other variables These variables included self-reports of handedness, gender and age.
3.1. Participants
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60
50 SlideG1
Twenty-three participants (16 females, average age ¼ 17.9; seven males, average age ¼ 18.1) were recruited from an undergraduate General Psychology class at the University of Central Florida. Participants were required to possess at least 20/40 corrected vision, and reportedly be free of known visual defects. Participants were screened for color blindness and static visual acuity and were compensated via either pay ($6/hour) or extra credit (2 points/hour), but not both. Most participants elected to receive extra credit. Almost all participants required 3 h to complete the experiment. Prior to taking part in the study, all participants were asked to complete a written informed consent form. 3.2. Procedure The procedure followed in this experiment is the same as described above. Participants in the experiment were exposed to the narrow range of velocities (60, 75 and 90 dps) and were referred to as Group I. 3.3. Results Two ANOVAs, one each for the two test modes used (‘‘slide’’ and ‘‘laser’’) by Group I, were performed on the data. The two ANOVAs exhibited very similar patterns with all main effects (i.e., sessions, speeds, sizes, replications, and orientations/letters) statistically significant (p generally < 0.000). Additionally, several of the same two-way interactions were significant in both ANOVAs. 4. Group II experiment
SlideG2
LaserG1
LaserG2
40 1
2
3
Session Fig. 1. Percent correct by session.
4.3. Results Two ANOVAs, one each for the two test modes used (‘‘slide’’ and ‘‘laser’’) by Group II, were performed on the data. The two ANOVAs exhibited very similar patterns with all main effects (i.e., sessions, speeds, sizes, replications, and orientations/letters) statistically significant (p generally < 0.000). Additionally, several of the same two-way interactions were significant in both ANOVAs. 5. Overall results of Groups I and II Because the four ANOVAs conducted on the two groups exhibited very similar patterns with all the main effects statistically significant, and because several of the same two-way interactions were also significant in all four ANOVAs, their means are presented on the same graphs. Fig. 1 shows the trend over sessions for the two groups for the two test modes (i.e., four comparisons). Both sets of ‘‘slide’’ scores (Groups I and II) improve gradually and regularly (w2%) over the three sessions. Both ‘‘laser’’ scores also improve regularly (w4%) over the three sessions. It may be seen that Group I, the group with the lower range of scores (60, 75 and 90), has higher percent correct scores than Group II, and ‘‘slide’’ scores show a higher percent correct than ‘‘laser’’. In Fig. 2, the relationship between stimulus speed (or velocity) and the participants’ performances are graphically displayed. As
4.1. Participants
100
90
Percent Correct
Twenty-five participants (10 females, average age ¼ 18.3; 15 males, average age ¼ 19) were recruited from an undergraduate General Psychology class at the University of Central Florida. Participants were required to possess at least 20/40 corrected vision, and reportedly be free of known visual defects. Participants were screened for color blindness and static visual acuity and were compensated via either pay ($6/hour) or extra credit (2 points/ hour), but not both. Most participants elected to receive extra credit. Almost all participants required 3 h to complete the experiment. Prior to taking part in the study, all participants were asked to complete a written informed consent form.
269
80
70
60
50
4.2. Procedure The procedure followed in this experiment is the same as described above. Participants in the experiment were exposed to the wide range of velocities (60, 90, and 120 dps) and were referred as Group II.
SlideG1
SlideG2
LaserG1
LaserG2
40 slow
medium
Presentation Speed Fig. 2. Percent correct by speed.
fast
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J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273
100
100
90
90
80
80
Percent Correct
Percent Correct
UL/M
70
60
50
UR/N
BL/V
BR/W
70
60
50 SlideG2
SlideG1
LaserG2
LaserG1
40
40 small
medium
large
SlideG1
Stimulus Size
SlideG2
LaserG1
LaserG2
Fig. 5. Percent correct by stimulus.
Fig. 3. Percent correct by size.
expected, within each task, the faster presentation velocities were more difficult for the participants and produced lower scores. It should be noted that both groups (I and II) and both methods (‘‘laser’’ and ‘‘slide’’) were tested at 60 dps and these show similar results (near 100% correct). Both groups (i.e., I and II) were also tested at 90 dps and differences between groups were statistically significant for ‘‘slide’’ (p < 0.02) and ‘‘laser’’ (p < 0.01) with Group I showing the better performances in both comparisons. As for target size, predictably, there is a better performance (higher percent correct) for larger targets for both tasks (‘‘slide’’ and ‘‘laser’’) for both groups (Fig. 3). While it may be seen that in Fig. 4 which represents percent correct by replication, three of the four curves show a slight tendency to decline within a session and one does not, in all cases the within session changes are <4%. We will be sensitive to task length in future work where we will attempt to study this and other procedural effects. With regard to the percent correct by stimulus, of the four orientations of the ‘‘slide’’ and the four letters of the ‘‘laser,’’ the right orientations, particularly the ‘‘45 orientation’’, appeared
100
Percent Correct
90
80
70
most difficult on the slide task. The laser task revealed that the ‘‘W’’ turned out to be the most difficult letter to identify, closely followed by the ‘‘V’’ (Fig. 5). 5.1. Within task correlations 5.1.1. Correlations of individual sessions Tables 1 and 2 show the within test (retest) correlations for the three sessions for the two groups. In all four matrices, the within test (retest reliability) correlations were significantly different from zero (p < 0.05), and, on the average, the highest retest correlations are found for laser/Group II and the lowest ones for slide/Group I. 5.1.2. Aggregation of data One of the ways to evaluate comparability between the two tests was to aggregate the scores and correlate them. Prior to combining these data, Lawley’s test for the equality of all retest correlations (Morrison, 1967) was applied and it was found that none of the intra-session correlations in the four retest correlation matrices showed evidence of significance (p > 0.10). This lack of significance of the cross-session correlations implies differential stability (Jones, 1980; Steiger, 1980), particularly when standard deviations over sessions are constant, as they were in this experiment. Furthermore, the means over sessions were monotonic (cf., Fig. 3), which appears to be a practice effect and may imply learning. But the improvement over sessions was small (w3%), well behaved, and it is arguable that the improvements did not appear to reflect differences in learning rate, although this question remains to be answered in future work. In any case, we considered that what we would gain in simplicity by aggregation of all the ‘‘slide’’ and ‘‘laser’’ data for each of the two groups would be of use in the comparison of the two tests as well as when comparing correlations between both sets of DVA scores and other variables.
60 Table 1 Correlations: slide and laser, Group I (60, 75, 90).
50 SlideG1
SlideG2
LaserG2
LaserG1
40 1
2
3
Replication Fig. 4. Percent correct by replication.
4
Correlations
Slide 1
Slide 2
Slide 3
Laser 1
Laser 2
Laser 3
Slide 1 Slide 2 Slide 3 Laser 1 Laser 2 Laser 3
1.0000 0.6582 0.4999 0.8070 0.5422 0.4663
0.6582 1.0000 0.7006 0.6504 0.6899 0.5054
0.4999 0.7006 1.0000 0.5653 0.6326 0.7245
0.8070 0.6504 0.5653 1.0000 0.7833 0.6339
0.5422 0.6899 0.6326 0.7833 1.0000 0.7789
0.4663 0.5054 0.7245 0.6339 0.7789 1.0000
J. Al-Awar Smither, R.S. Kennedy / Applied Ergonomics 41 (2010) 266–273 Table 2 Correlations: slide and laser, Group II (60, 90, 120).
Table 4 Correlations: DVA with other variables, Group I (60, 75, 90).
Correlations
Slide 1
Slide 2
Slide 3
Laser 1
Laser 2
Laser 3
Slide 1 Slide 2 Slide 3 Laser 1 Laser 2 Laser 3
1.0000 0.9008 0.7762 0.7222 0.6478 0.5459
0.9008 1.0000 0.8112 0.7935 0.7465 0.5991
0.7762 0.8112 1.0000 0.6901 0.6310 0.5034
0.7222 0.7935 0.6901 1.0000 0.8918 0.7770
0.6478 0.7465 0.6310 0.8918 1.0000 0.8781
0.5459 0.5991 0.5034 0.7770 0.8781 1.0000
Key: r ¼ 0.39 (p ¼ 0.05); r ¼ 0.52 (p ¼ 0.01); r ¼ 0.66 (p ¼ 0.001).
Correlations Handedness Gender Age SLIDE LASER
0.2462 0.2659
5.2.2. Averaging correlations Another way to examine the relationship between performances on the two tasks is to average correlations (Dunlap et al., 1986; Bittner et al., 1982) rather than correlating averages, as what was done above with aggregation of the three sessions of data. In addition to the retest correlations, Table 1 (Group I) and Table 2 (Group II) also show the between test (cross-task) correlations of ‘‘laser’’ and ‘‘slide’’. It may be seen that all nine cross-task correlations in each table are statistically significant (p < 0.05). The retest correlations of Tables 1 and 2 were then averaged separately for ‘‘laser’’ and ‘‘slide’’ and for the two Groups and then entered into the diagonal of Table 3. Then the nine between task correlations were likewise averaged and entered into the superdiagonal of Table 3. Finally the correction for attenuation formula (Spearman, 1904):
r12 R12 ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi r11 r22
(1)
was used to correct for reliability attenuation of the measures (cf., also Gulliksen, 1987). In the diagonal, in parentheses, are the average retest reliability for the two groups for the ‘‘laser’’ and ‘‘slide’’. Above the diagonal is the average cross-task correlation between ‘‘laser’’ and ‘‘slide’’ for each group and below the diagonal is the corrected for attenuation correlation. It may be seen that ‘‘laser’’/’’slide’’ comparisons, corrected for attenuation, are R ¼ 0.92 for Group I and R ¼ 0.78 for Group II, which signify a close correspondence between the two tests and imply that ‘‘laser’’ could be used instead of the traditional slides with minimal loss in validity. 5.3. Other findings Tables 4 and 5 show correlations between the aggregated DVA measures and the other variables. While in both groups ‘‘laser’’ and ‘‘slide’’ are correlated with each other, neither measure, in either group, is related to gender or handedness. Visual span, the test most obviously like DVA, correlated with ‘‘slide’’ and ‘‘laser’’ for Table 3 Correlations: correction for attenuation.
Slide Laser
Group II
Color blindness
Static visual
0.2083 0.1413
0.1842 0.1463
Table 5 Correlations: DVA with other variables, Group II (60, 90, 120). Correlations Handedness Gender Age
5.2.1. Aggregation of data All the data for three sessions, three velocities, three sizes, four replications, and four orientations, were summed for each participant for the two tasks independently (‘‘laser’’ and ‘‘slide’’) and these data were correlated over all the participants separately for Group I and for Group 2. These two correlations between ‘‘laser’’ and ‘‘slide’’ were r ¼ 0.54 and r ¼ 0.70 for Groups I and II, respectively.
Visual span
0.1138 0.0395 0.1415 0.3769 0.0222 0.0664
5.2. Between task correlations
Group I
271
SLIDE LASER
0.3008 0.0396
Visual span
0.0197 0.1103 0.4535 0.2632 0.1934 0.3833
Color blindness
Static visual
0.2297 0.2604
0.1615 0.0443
Key: r ¼ 0.39 (p ¼ 0.05); r ¼ 0.52 (p ¼ 0.01); r ¼ 0.66 (p ¼ 0.001).
Group II (p < 0.05), but did not relate to either task for Group I. Relatedly, static (i.e., Snellen) acuity and color vision scores were zero in all four DVA comparisons. 6. Discussion and conclusions The primary objective of this project was the development of a reasonably priced, highly flexible, portable, valid and reliable instrument for the assessment of DVA. The major question asked was whether implementation of targets via laser would be able to provide comparable data to the more traditional Landolt C presentation. To answer this empirical question a device patterned after the Ludvigh and Miller (1953) and Long and Penn (1987) devices was assembled. Then, using slightly different velocity parameters, two formal studies were conducted with both devices employing about 25 participants for each. When the two tests in the two groups were compared, using two analytic approaches, strong and significant correlations between the two tasks were found. If the scores from the traditional device can be considered the standard, it appears that the measures from the laser system may be considered comparable for the comparisons made. This implies that development of a portable, flexible device is feasible. While letter targets were employed in this work, the laser offers the opportunity to experiment with many other forms, luminance, contrasts, sizes, etc. In the future, the plan is to explore much of this experimental ‘‘space’’ in psychophysical studies. As further evidence of the comparability of the two DVA test methods, it also appears that essentially the same main effects were significant in both devices and performances were similar over the two devices and in both groups. Although the sample sizes were small, the data sets were largely regular and the two groups provided a form of cross validation for each other since stimulus characteristics appeared to be more of a factor than ‘‘laser’’ versus ‘‘slide’’ presentation. Thus there were some inferences that could be made from the data as collected. First, and not surprisingly, the letter recognition task may have been more difficult than the orientation detection task, and thereby partly explains the differences in performance where for the same velocities ‘‘slide’’ scores were better than ‘‘laser’’ scores. Next, there appeared to be a context effect, whereby there were small differences between the performances of the two groups at their respective 90 dps condition, with the group having the higher range of scores doing less well than did the group with the lower range of velocities. 6.1. Additional factors
Slide
Laser
Slide
Laser
(0.6196) 0.9212
0.5373 (0.7320)
(0.8294) 0.7785
0.6973 (0.8490)
There is other work still to be carried out in order to produce an alternative to the ‘‘slide’’ method of DVA testing. For example,
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researchers could improve on the metric properties (reliability, stability) of the laser device and they could also generalize these findings from the narrow range of stimulus characteristics used in this study (velocities, shapes, sizes, contrasts, brightness, etc.). Furthermore, they could also examine time course changes which may result from fatigue and tedium of too long sessions. Additional findings to be explored further include what appeared to be a practice or learning effect over the three sessions. This result is consistent with what others have reported in the literature (e.g., Ludvigh and Miller, 1954, 1955) and should be further explored. If DVA performance can be improved by practice, and if DVA is indeed involved in the performance of various tasks like driving, perhaps training can be employed for persons who may have lost some function through injury or aging. Additional stimulus factors that might prove to be of interest are the type of stimulus motion (linear versus accelerative) and the form of the target (Vernier targets, other objects, etc.). Furthermore, test administrators must be able to adjust or program the dependent measure (e.g., target size) in a psychometrically sound manner that permits the rapid determination of a naive observer’s score (e.g., threshold size) for a given set of conditions. Other stimulus variables include target (i.e., screen) distance and background characteristics and being able to change the target shape after the eye is entrained and is tracking the target (i.e., within 5 msec). Additionally, the laser would permit the generation of new and more realistic tasks that would also measure dynamic visual acuity. These tasks could be presented on a personal-computer setup. It would also be useful to establish how DVA is distributed in the population or whether like visual acuity, it might be that most people have an equivalent amount unless there was damage to the system. Although the homogeneity of this group could be expected to cause the range of scores to be restricted, correlations were still obtained between DVA measured via both ‘‘slide’’ and ‘‘laser’’ methods. Doubtless this range restriction also influenced correlations with other variables and a broader attempt should be made in future work to examine how several visual and cognitive tests correlate. This research seems to indicate that both DVA tests correlate with each other, but not with three other visual tests. This lends support to the contention (Kandel et al., 1995) of a separate smooth pursuit system. At the same time, individual differences in DVA ability, even in a homogeneous population, are fairly large, and thus DVA appears to be a useful target for further study.
6.2. Advantages of laser DVA devices Laser has several advantages over the traditional device since the laser does not work from fixed pictures which need to be photographed in advance and may entail increased experimental time to run because of slowness of presentations. The chief advantage of the laser system is that it is flexible, and images can be modified and scaled easily and so different forms and shapes may be used. In a laser system one can vary presentation speed easily and accurately, presentations of the stimulus can be tracked easily and there is a minimum of moving parts. Other advantages include the fact that a laser can project over a large area, thereby allowing for large stimuli that traverse a larger visual angle. Next, virtually any type of dotted or lined stimuli can be projected (e.g., simple spot, vertical or horizontal lines, boxes, cars, etc.). Laser also has far greater flexibility in display of dynamic stimuli. Rather than displaying only horizontal translation, it is capable of displaying stimuli that change size and translate at the same time. Therefore, the stimulus can change its acuity demand after the eye is entrained in motion. This latter issue has always been a problem
with the more conventional device and study of the implications can refine what we know about DVA. 6.3. Future research A DVA test, perhaps as part of a battery of visual tests, seems to be a useful addition to the array of existing measures used in driver research and education. Also, if supported in a larger study, these findings are an extremely important step in establishing the hypothesized link between this visual ability and automobile crashes, especially as older drivers are concerned. Aging and driving crashes are related to DVA scores. Together, the results suggest a model of age effects on visual and cognitive abilities and associated components of driving which can be used to guide future research in this area. Our future research plans include: (1) conducting a replication of the psychometrics of this study but broadening the stimuli presented and creating normative data with a larger number of participants; using a large number of visual targets; (2) determining whether a sample of participants have relationships between DVA thresholds and automobile crash history; (3) examining the effects of age and blood alcohol on DVA with self-reports of crashes; and (4) extending the predictive validities to job performance on a high fidelity simulator. 6.4. Conclusions The goal of this research was to develop a valid and reliable portable DVA system using a low-energy laser. The laser device developed was compared to a traditional DVA device in two withinsubjects, repeated measures designs. The findings of these studies indicated that: (1) retest reliabilities of the two DVA devices were comparable and higher with the laser; (2) average correlations between the two devices were r ¼ 0.62 (p < 0.01) and r ¼ 0.65 (p < 0.01) for the two devices respectively; and (3) after correction for reliability attenuation these correlations improved to r ¼ 0.92 and r ¼ 0.78. These findings indicate that a flexible and portable DVA laser device can be developed to measure the same construct as the more traditional bulky DVA device. As such, this device could be used to assess individual DVA more easily and to serve as a predictor of visual requirements in many real-world settings, especially driving. References Bittner Jr., A.C., Dunlap, W.P., Jones, M.B., 1982. Averaged cross-correlations with differentially-stable variables: fewer participants required with repeated measures. Proceedings of the Human Factors Society 26 (5), 349–353. Bridgeman, B., 1995. Direction constancy in rapidly refreshed video displays. Journal of Vestibular Research 5 (6), 393–398. Burg, A., 1966. Visual acuity as measured by dynamic and static tests: a comparative evaluation. Journal of Applied Psychology 50, 460–466. Burg, A., 1967. The Relationship Between Vision Test Scores and Driving Record: General Findings. (Report No. 67-24). University of California, Department of Engineering, Los Angeles, CA. Burg, A., 1968. Vision Test Scores and Driving Record: Additional Findings. (Report No. 68-27). University of California, Department of Engineering, Los Angeles, CA. Burg, A., 1971. Vision and driving: a report on research. Human Factors 13, 79–87. Committee on Vision of the National Research Council (U.S.), 1985. Emergent Techniques for the Assessment of Visual Performance. National Academy Press, Washington, DC. DeKlerk, L.F.W., Ernst, J.Th., Hoogerheide, J., 1964. The dynamic visual acuity of 30 selected pilots. Aeromedica Acta 9, 129–136. Dunlap, W.P., Silver, N.C., Bittner, A.C., 1986. Estimating reliability with small samples: increased precision with averaged correlations. Human Factors 28 (6), 685–690. Dvorine, E., 1953. Dvorine Pseudo-Isochromatic Plates. Harcourt, second ed. Brace & World, Inc., New York. Farrimond, T., 1967. Visual and auditory performance variations with age: some implications. Australian Journal of Psychology 19, 193–201. Graham, C.H. (Ed.), 1965. Vision and Visual Perception. John Wiley & Sons, Inc, New York. Gulliksen, H., 1987. Theory of Mental Tests. Lawrence-Erlbaum Associates, Hillsdale, NJ.
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