Multimodal Features for Detection of Driver Stress and Fatigue: Review

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dc.contributor.authorNěmcová, Andreacs
dc.contributor.authorSvozilová, Veronikacs
dc.contributor.authorBucsuházy, Kateřinacs
dc.contributor.authorSmíšek, Radovancs
dc.contributor.authorMézl, Martincs
dc.contributor.authorHesko, Branislavcs
dc.contributor.authorBelák, Michalcs
dc.contributor.authorBilík, Martincs
dc.contributor.authorMaxera, Pavelcs
dc.contributor.authorSeitl, Martincs
dc.contributor.authorDominik, Tomášcs
dc.contributor.authorSemela, Marekcs
dc.contributor.authorŠucha, Matúšcs
dc.contributor.authorKolář, Radimcs
dc.coverage.issue6cs
dc.coverage.volume22cs
dc.date.issued2021-06-01cs
dc.description.abstractDriver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios.en
dc.formattextcs
dc.format.extent3214-3233cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationIEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. 2021, vol. 22, issue 6, p. 3214-3233.en
dc.identifier.doi10.1109/TITS.2020.2977762cs
dc.identifier.issn1558-0016cs
dc.identifier.orcid0000-0003-1801-7057cs
dc.identifier.orcid0000-0001-5184-8923cs
dc.identifier.orcid0000-0003-1247-6148cs
dc.identifier.orcid0000-0003-0413-3604cs
dc.identifier.orcid0000-0002-4147-8727cs
dc.identifier.orcid0000-0001-7126-0617cs
dc.identifier.orcid0000-0002-6923-8725cs
dc.identifier.orcid0000-0003-3796-4658cs
dc.identifier.orcid0000-0001-9461-9477cs
dc.identifier.orcid0000-0003-3716-1062cs
dc.identifier.orcid0000-0002-0469-6397cs
dc.identifier.other163233cs
dc.identifier.researcheridAAH-1590-2021cs
dc.identifier.researcheridAAG-5924-2019cs
dc.identifier.researcheridF-5329-2017cs
dc.identifier.researcheridA-2336-2016cs
dc.identifier.researcheridJ-5251-2016cs
dc.identifier.researcheridJ-5266-2016cs
dc.identifier.researcheridV-4736-2017cs
dc.identifier.researcheridJ-4907-2016cs
dc.identifier.researcheridC-8547-2014cs
dc.identifier.scopus6507784572cs
dc.identifier.scopus57194560385cs
dc.identifier.scopus57188873046cs
dc.identifier.scopus36477866400cs
dc.identifier.scopus57205166450cs
dc.identifier.scopus56578277800cs
dc.identifier.scopus57205167913cs
dc.identifier.scopus56578709000cs
dc.identifier.urihttp://hdl.handle.net/11012/195664
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofIEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMScs
dc.relation.urihttps://ieeexplore.ieee.org/document/9031734cs
dc.rights(C) IEEEcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1558-0016/cs
dc.subjectdriver fatigueen
dc.subjectdriver stressen
dc.subjecttraffic accidenten
dc.subjectphysiological signalsen
dc.subjectmultimodal featuresen
dc.titleMultimodal Features for Detection of Driver Stress and Fatigue: Reviewen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionacceptedVersionen
sync.item.dbidVAV-163233en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:39:44en
sync.item.modts2025.01.17 15:23:55en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav biomedicínského inženýrstvícs
thesis.grantorVysoké učení technické v Brně. . Univerzita Palackého v Olomoucics
thesis.grantorVysoké učení technické v Brně. Ústav soudního inženýrství. Odbor znalectví ve strojírenství, analýza dopravních nehod a oceňování motorových vozidelcs
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Odbor znalectví ve strojírenství, analýza dopravních nehod a oceňování motorových vozidel
Ústav biomedicínského inženýrství