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. 2009 Jan 1;21(S1):S123-S129.
doi: 10.1080/08995600802554789.

Using Time Perception to Measure Fitness for Duty

Affiliations

Using Time Perception to Measure Fitness for Duty

David M Eagleman. Mil Psychol. .

Abstract

Assessing fitness for duty (FFD) typically requires expensive equipment and large time windows. Here we capitalize on basic principles of human time perception to build a portable software package that can quickly and efficiently test for excessive fatigue or traumatic brain injury. Time perception involves a collaboration of many brain areas, and we hypothesize that generalized damage to the brain can be rapidly assessed by subtle disorders in simple timing tasks. We aim to produce an inexpensive, portable device for rapid detection of fatigue or brain injury both in the clinic and on the field.

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Figures

FIGURE 1
FIGURE 1
Using alternating images to measure the speed of alternation at which observers can report numbers. (a) When a digit is alternated slowly with its negative image, it is easy to identify. (b) As the rate of alternation increases, the patterns fuse into a uniform field, indistinguishable from any other digit and its negative (see Stetson et al., 2007).
FIGURE 2
FIGURE 2
Measuring four aspects of timing and time perception using a simple video game. (a) The green square “jumps” to a new location each time it is clicked. On some trials it jumps just before being clicked, and subjects report when this occurred. (b) Representative data. The blue curve represents 0-ms delay block; the red curve represents 200-ms “injected delay” block. The shift in the point of subjective equivalence (PSE) was 56 ms. (c) Average recalibration (difference between red and blue curves) shift for 6 subjects.
FIGURE 3
FIGURE 3
Measuring the brain’s temporal responses: repeated stimuli subjectively proliferate less than random stimuli. (a) Example sequences of stimulus presentation and perceived numerosity for repeated and random stimuli. (b) Number of characters perceived to be present for repeated and random stimuli. Participants report more characters present on screen when the stimuli are different than when they are repeated (n = 31; error bars indicate SEM).

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