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Title: | A pre-drive ocular assessment predicts alertness and driving impairment: A naturalistic driving study in shift workers. | Austin Authors: | Mulhall, Megan D;Cori, Jennifer M ;Sletten, Tracey L;Kuo, Jonny;Lenné, Michael G;Magee, Michelle;Spina, Marie-Antoinette;Collins, Allison L ;Anderson, Clare;Rajaratnam, Shantha M W;Howard, Mark E | Affiliation: | Monash University Accident Research Centre, Monash University, Victoria, Australia Institute for Breathing and Sleep, Austin Health, Victoria, Australia Seeing Machines Ltd., 80 Mildura St., Fyshwick, ACT, Australia School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia Cooperative Research Centre for Alertness, Safety and Productivity, Melbourne, Australia |
Issue Date: | Feb-2020 | Date: | 2019-12-02 | Publication information: | Accident; Analysis and Prevention 2020; 135: 105386 | 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. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/22230 | DOI: | 10.1016/j.aap.2019.105386 | Journal: | Accident; Analysis and Prevention | PubMed URL: | 31805427 | Type: | Journal Article | Subjects: | Driving impairment Drowsy driving Fatigue Ocular measures Predicting performance |
Appears in Collections: | Journal articles |
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