@article{ref1,
title="A pre-drive ocular assessment predicts alertness and driving impairment: a naturalistic driving study in shift workers",
journal="Accident analysis and prevention",
year="2019",
author="Sletten, Tracey L. and Cori, Jennifer and Mulhall, Megan D. and Kuo, Jonny and Lenné, Michael G. and Magee, Michelle and Spina, Marie-Antoinette and Collins, Allison and Anderson, Clare and Rajaratnam, Shantha M. W. and Howard, Mark E.",
volume="135",
number="",
pages="e105386-e105386",
abstract="Sleepiness is a major contributor to motor vehicle crashes and shift workers are particularly vulnerable. There is currently no validated objective field-based measure of sleep-related impairment prior to driving. Ocular parameters are promising markers of continuous driver alertness in laboratory and track studies, however their ability to determine fitness-to-drive in naturalistic driving is unknown. This study assessed the efficacy of a pre-drive ocular assessment for predicting sleep-related impairment in naturalistic driving, in rotating shift workers. Fifteen healthcare workers drove an instrumented vehicle for 2 weeks, while working a combination of day, evening and night shifts. The vehicle monitored lane departures and behavioural microsleeps (blinks >500 ms) during the drive. Immediately prior to driving, ocular parameters were assessed with a 4-min test. Lane departures and behavioural microsleeps occurred on 17.5 % and 10 % of drives that had pre-drive assessments, respectively. Pre-drive blink duration significantly predicted behavioural microsleeps and showed promise for predicting lane departures (AUC = 0.79 and 0.74). Pre-drive percentage of time with eyes closed had high accuracy for predicting lane departures and behavioural microsleeps (AUC = 0.73 and 0.96), although was not statistically significant. Pre-drive psychomotor vigilance task variables were not statistically significant predictors of lane departures. Self-reported sleep-related and hazardous driving events were significantly predicted by mean blink duration (AUC = 0.65 and 0.69). Measurement of ocular parameters pre-drive predict drowsy driving during naturalistic driving, demonstrating potential for fitness-to-drive assessment in operational environments.<br><br>Copyright © 2019 Elsevier Ltd. All rights reserved.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2019.105386",
url="http://dx.doi.org/10.1016/j.aap.2019.105386"
}