Advancing our Understanding of Performance during Sleep Deprivation

Sleep deprivation is a concern in professional, military, and personal settings and can potentially lead to critical, life threatening errors. Predicting a person’s behavior under the effects of sleep deprivation allows for the mitigation of risk due to reduced performance. The objectives of this dissertation are 1) to examine the role of sleep deprivation on cognitive and motor performance with the goal of contributing to a predictive model of complex real-world tasks, and 2) to explore non-invasive and non-disruptive physiological correlates of sleep deprivation through eye-tracking. Currently lacking in literature, and consequently from predictive models, are the generalized effects that sleep deprivation has on performance. To approach this problem, sets of motor control and cognitive tasks were designed to evaluate human performance under the effects of sleep deprivation. Models for these tasks were developed to assess their current capacity to predict performance. Sleep deprivation studies for these tasks were run to measure the cognitive effects of sleep deprivation, and explore eye tracking as a physiological correlate. The findings in this dissertation suggest that current models predict human performance of simple tasks, but fail to adequately simulate human performance during higher complexity tasks. Consequently, this work provides both experimental results and a framework from which more accurate models with higher predictive power can be designed. Finally, it was found that multiple eye-tracking measures correlated with the performance of various cognitive tasks, implying the potential use of such measures as alternate predictors of performance while under the effects of sleep deprivation