Toward emotion recognition in car-racing drivers: A biosignal processing approach

dc.contributor.authorKatsis, C. D.en
dc.contributor.authorKatertsidis, N.en
dc.contributor.authorGaniatsas, G.en
dc.contributor.authorFotiadis, D. I.en
dc.date.accessioned2015-11-24T17:31:42Z
dc.date.available2015-11-24T17:31:42Z
dc.identifier.issn1083-4427-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13614
dc.rightsDefault Licence-
dc.subjectadaptive neuro-fuzzy inference system (anfis)en
dc.subjectbiosignal processingen
dc.subjectemotion recognitionen
dc.subjectsupport vector machines (svms)en
dc.subjectwearable systemen
dc.subjectphysiological signalsen
dc.subjectfacial expressionsen
dc.titleToward emotion recognition in car-racing drivers: A biosignal processing approachen
heal.abstractIn this paper, we present a methodology and a wearable system for the evaluation of the emotional states of car-racing drivers. The proposed approach performs an assessment of the emotional states using facial electromyograms, electrocardiogram, respiration, and electrodermal activity. The system consists of the following: 1) the multisensorial wearable module; 2) the centralized computing module; and 3) the system's interface. The system has been preliminary validated by using data obtained from ten subjects in simulated racing conditions. The emotional classes identified are high stress, low stress, disappointment, and euphoria. Support vector machines (SVMs) and adaptive neuro-fuzzy inference system (ANFIS) have been used for the classification. The overall classification rates achieved by using tenfold cross validation are 79.3% and 76.7% for the SVM and the ANFIS, respectively.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primaryDoi 10.1109/Tsmca.2008.918624-
heal.identifier.secondary<Go to ISI>://000258183000001-
heal.journalNameIeee Transactions on Systems Man and Cybernetics Part a-Systems and Humansen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2008-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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