Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/17126
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dc.contributor.authorShiferaw, Brook A-
dc.contributor.authorDowney, Luke A-
dc.contributor.authorWestlake, Justine-
dc.contributor.authorStevens, Bronwyn-
dc.contributor.authorRajaratnam, Shantha M W-
dc.contributor.authorBerlowitz, David J-
dc.contributor.authorSwann, Phillip-
dc.contributor.authorHoward, Mark E-
dc.date2018-
dc.date.accessioned2018-02-07T04:44:55Z-
dc.date.available2018-02-07T04:44:55Z-
dc.date.issued2018-02-02-
dc.identifier.citationScientific Reports 2018; 8(1): 2220-
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/17126-
dc.description.abstractPerformance decrement associated with sleep deprivation is a leading contributor to traffic accidents and fatalities. While current research has focused on eye blink parameters as physiological indicators of driver drowsiness, little is understood of how gaze behaviour alters as a result of sleep deprivation. In particular, the effect of sleep deprivation on gaze entropy has not been previously examined. In this randomised, repeated measures study, 9 (4 male, 5 female) healthy participants completed two driving sessions in a fully instrumented vehicle (1 after a night of sleep deprivation and 1 after normal sleep) on a closed track, during which eye movement activity and lane departure events were recorded. Following sleep deprivation, the rate of fixations reduced while blink rate and duration as well as saccade amplitude increased. In addition, stationary and transition entropy of gaze also increased following sleep deprivation as well as with amount of time driven. An increase in stationary gaze entropy in particular was associated with higher odds of a lane departure event occurrence. These results highlight how fatigue induced by sleep deprivation and time-on-task effects can impair drivers' visual awareness through disruption of gaze distribution and scanning patterns.-
dc.language.isoeng-
dc.titleStationary gaze entropy predicts lane departure events in sleep-deprived drivers.-
dc.typeJournal Article-
dc.identifier.journaltitleScientific Reports-
dc.identifier.affiliationCentre for Human Psychopharmacology, Swinburne University of Technology, Hawthorn, Australia-
dc.identifier.affiliationInstitute for Breathing and Sleep, Austin Health, Heidelberg, Victoria, Australia-
dc.identifier.affiliationMonash Institute of Cognitive and Clinical Neurosciences and School of Psychological Sciences, Monash University, Clayton, Victoria, Australia-
dc.identifier.affiliationUniversity of Melbourne, Melbourne, Australia-
dc.identifier.affiliationVicRoads, Kew, Australia-
dc.identifier.pubmedurihttps://pubmed.ncbi.nlm.nih.gov/29396509-
dc.identifier.doi10.1038/s41598-018-20588-7-
dc.identifier.orcid0000-0003-2543-8722-
dc.identifier.pubmedid29396509-
dc.type.austinJournal Article-
local.name.researcherBerlowitz, David J
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeJournal Article-
crisitem.author.deptInstitute for Breathing and Sleep-
crisitem.author.deptPhysiotherapy-
crisitem.author.deptInstitute for Breathing and Sleep-
crisitem.author.deptData Analytics Research and Evaluation (DARE) Centre-
crisitem.author.deptInstitute for Breathing and Sleep-
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