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Free Content Oculomotor Measures as Predictors of Performance During Sleep Deprivation

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McClelland LE, Pilcher JJ, Moore DD. Oculomotor measures as predictors of performance during sleep deprivation. Aviat Space Environ Med 2010; 81:833–42.

Introduction: Studies have indicated that working under sleep deprivation conditions results in deficits in performance on various tasks. Few studies, however, have attempted to find a measure for predicting performance changes under sleep deprivation conditions. The current study examined whether oculomotor measures could predict changes in performance under non-sleep deprivation and acute short-term sleep deprivation conditions. Methods: Oculomotor measures and performance were examined during five testing sessions in each study. In the non-sleep deprivation study (N = 23) the testing sessions took place during 2 consecutive days. The sleep deprivation study (N = 26) took place in an 18-h sustained operations period during the night of sleep deprivation. Results: Under non-sleep deprivation conditions, pupil diameter significantly predicted performance on grammatical reasoning (B = 0.360) and constriction latency significantly predicted performance on combined tasks (B = 0.182). Under sleep deprivation conditions, diameter, constriction latency, and saccadic velocity significantly predicted performance on a psychomotor vigilance task (B = −21.002, B = −23.126, B = −18.028, respectively). Overall, oculomotor measures better predicted performance changes under sleep deprivation conditions and better predicted performance decrements on vigilance-based tasks than cognitive tasks under acute sleep deprivation conditions. Discussion: The current research suggests saccadic velocity and pupil diameter may be the most useful predictors of performance under sleep deprivation conditions, perhaps because these measures are largely controlled by involuntary neural components that slow during sleep deprivation. These data support research suggesting that saccadic velocity and pupil diameter detect excessive sleepiness and predict performance decrements under sleep deprivation conditions using additional oculomotor measures and a non-sleep deprivation comparison group.

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Keywords: fatigue; hierarchical linear modeling; stress; sustained operations

Document Type: Research Article

Publication date: 2010-09-01

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