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|Title:||Eye-Blink Parameters Detect On-Road Track-Driving Impairment Following Severe Sleep Deprivation.|
|Authors:||Shekari Soleimanloo, Shamsi;Wilkinson, Vanessa E;Cori, Jennifer M;Westlake, Justine;Stevens, Bronwyn;Downey, Luke A;Shiferaw, Brook A;Rajaratnam, Shantha M W;Howard, Mark E|
|Affiliation:||School of Psychological Sciences, Monash University, Australia|
Institute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia
Centre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, Australia
Department of Medicine, University of Melbourne, Australia
Department of Respiratory and Sleep Medicine, Austin Health, Heidelberg, Victoria, Australia
|Citation:||Journal of clinical sleep medicine : JCSM 2019; 15(9): 1271-1284|
|Abstract:||Drowsiness leads to 20% of fatal road crashes, while inability to assess drowsiness has hampered drowsiness interventions. This study examined the accuracy of eye-blink parameters for detecting drowsiness related driving impairment in real time. Twelve participants undertook two sessions of 2-hour track-driving in an instrumented vehicle following a normal night's sleep or 32 to 34 hours of extended wake in a randomized crossover design. Eye-blink parameters and lane excursion events were monitored continuously. Sleep deprivation increased the rates of out-of-lane driving events and early drive terminations. Episodes of prolonged eyelid closures, blink duration, the ratio of amplitude to velocity of eyelid closure, and John's Drowsiness Score (JDS, a composite score) were also increased following sleep deprivation. A time-on-task (drive duration) effect was evident for out-of-lane events rate and most eye-blink parameters after sleep deprivation. The JDS demonstrated the strongest association with the odds of out-of-lane events in the same minute, whereas measures of blink duration and prolonged eye closure were stronger indicators of risk for out-of-lane events over longer periods of 5 minutes and 15 minutes, respectively. Eye-blink parameters also achieved moderate accuracies (specificities from 70.12% to 84.15% at a sensitivity of 50%) for detecting out-of-lane events in the same minute, with stronger associations over longer timeframes of 5 minutes to 15 minutes. Eyelid closure parameters are useful tools for monitoring and predicting drowsiness-related driving impairment (out-of-lane events) that could be utilized for monitoring drowsiness and assessing the efficacy of drowsiness interventions. This study is registered with the Australian New Zealand Clinical Trial Registry (ANCTR), http://www.anzctr.org.au/TrialSearch.aspx ACTRN12612000102875.|
|Appears in Collections:||Journal articles|
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