Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6162
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dc.contributor.authorNassehi, Farhad-
dc.contributor.authorErdoğdu, Başak-
dc.contributor.authorŞişman, Sena-
dc.contributor.authorSağlam, Yağmur-
dc.contributor.authorEroğul, Osman-
dc.date.accessioned2021-09-11T15:35:08Z-
dc.date.available2021-09-11T15:35:08Z-
dc.date.issued2020en_US
dc.identifier.citationMedical Technologies National Congress (TIPTEKNO) -- NOV 19-20, 2020 -- ELECTR NETWORKen_US
dc.identifier.isbn978-1-7281-8073-1-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6162-
dc.description.abstractTopic of self-driving mode and transition to this mode is one of the trend topics of biomedical engineering and artificial intelligence studies. Sleeplessness and sleep efficiency to cause inattention in driving and accidents. This study aimed to investigate convenient time to transit self-driving mode respect to number of accidents and sleep efficiency of driver by using Support Vector Machines and K-Nearest neighbors classification algorithms to reduce the accidents. Approximate entropy and Lyapunov exponent for Electroencephalography and dominant frequency, ratio of power of high frequency to low frequency, area under the curve and derivative respiration signals were extracted. This proposal method achieves 93.33% and 100% accuracies to classify drivers and transit car to self-driving mode respect to two criteria.en_US
dc.description.sponsorshipBiyomedikal ve Klinik Muhendisligi Dernegi, Izmir Ekonomi Univ, Izmir Katip Celebi Univen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2020 Medical Technologies Congress (Tiptekno)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectsleeplessnessen_US
dc.subjectelectroencephalogramen_US
dc.subjectself-drivingen_US
dc.subjectApproximate entropyen_US
dc.subjectLyapunov exponenten_US
dc.titleA Study On Finding The Optimal Time For Automatic Transition To Self-Driving Modeen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Biomedical Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümütr_TR
dc.identifier.wosWOS:000659419900030en_US
dc.identifier.scopus2-s2.0-85099439770en_US
dc.institutionauthorEroğul, Osman-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conferenceMedical Technologies National Congress (TIPTEKNO)en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.2. Department of Biomedical Engineering-
Appears in Collections:Biyomedikal Mühendisliği Bölümü / Department of Biomedical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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