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EEG-based mental fatigue alarm system using weighted-frequency index

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dc.contributor.authorYunyong Punsawaden_US
dc.contributor.authorSittichai Aempedchren_US
dc.contributor.authorYodchanan Wongsawaten_US
dc.contributor.authorManukid Parnichkunen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherAsian Institute of Technology Thailanden_US
dc.date.accessioned2018-09-24T08:56:22Z
dc.date.available2018-09-24T08:56:22Z
dc.date.issued2010-12-01en_US
dc.description.abstractMental fatigue is another major cause of the serious car accidents. Ability to early predict the mental fatigue phenomenon is hence one of the challenging problems in brain-computer interface (BCI). In this paper, we propose the practical EEG-based mental fatigue alarm system including the weighted-frequency index of the linear combination among EEG theta, alpha and beta rhythms. The proposed system is tested with the simulated driving situations. By using only 1-channel EEG at the temporal area of the brain, more than 90% of prediction accuracies are reported compared to the opinion scores of the users.en_US
dc.identifier.citationAPSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. (2010), 193-196en_US
dc.identifier.other2-s2.0-79958169810en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/28977
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79958169810&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleEEG-based mental fatigue alarm system using weighted-frequency indexen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79958169810&origin=inwarden_US

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