Real-Time Driver's Stress Event Detection

dc.contributor.authorRigas, G.en
dc.contributor.authorGoletsis, Y.en
dc.contributor.authorFotiadis, D. I.en
dc.date.accessioned2015-11-24T17:05:40Z
dc.date.available2015-11-24T17:05:40Z
dc.identifier.issn1524-9050-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/11361
dc.rightsDefault Licence-
dc.subjectbayesian networks (bns)en
dc.subjectdriver stressen
dc.subjectdriving environmenten
dc.subjectkalman filteren
dc.subjectphysiological signalsen
dc.subjectsignalsen
dc.titleReal-Time Driver's Stress Event Detectionen
heal.abstractIn this paper, a real-time methodology for the detection of stress events while driving is presented. The detection is based on the use of physiological signals, i.e., electrocardiogram, electrodermal activity, and respiration, as well as past observations of driving behavior. Features are calculated over windows of specific length and are introduced in a Bayesian network to detect driver's stress events. The accuracy of the stress event detection based only on physiological features, evaluated on a data set obtained in real driving conditions, resulted in an accuracy of 82%. Enhancement of the stress event detection model with the incorporation of driving event information has reduced false positives, yielding an increased accuracy of 96%. Furthermore, our methodology demonstrates good adaptability due to the application of online learning of the model parameters.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primaryDoi 10.1109/Tits.2011.2168215-
heal.identifier.secondary<Go to ISI>://000300846700021-
heal.identifier.secondaryhttp://ieeexplore.ieee.org/ielx5/6979/6157683/06036175.pdf?tp=&arnumber=6036175&isnumber=6157683-
heal.journalNameIeee Transactions on Intelligent Transportation Systemsen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2012-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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