Sleepiness and Safety: Where Biology Needs Technology.

Sleep Biol Rhythms

Division of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Published: April 2014

AI Article Synopsis

  • Maintaining alertness and performance during sleep loss and circadian misalignment is essential and necessitates fatigue management technologies.
  • Key challenges include individual variations in vulnerability to fatigue, errors in self-assessing fatigue levels, and the need for recovery sleep.
  • Emerging technologies focus on optimizing work schedules with personalized biomathematical models and tools for detecting fatigue, such as the Psychomotor Vigilance Test (PVT) and monitoring eyelid closure patterns, to enhance safety in high-risk occupations.

Article Abstract

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061704PMC
http://dx.doi.org/10.1111/sbr.12067DOI Listing

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