Facial expression recognition with sEMG method

dc.contributor.authorMingzhe Jiang
dc.contributor.authorAmir-Mohammad Rahmani
dc.contributor.authorTomi Westerlund
dc.contributor.authorPasi Liljeberg
dc.contributor.authorHannu Tenhunen
dc.contributor.organizationfi=matemaattis-luonnontieteellinen tiedekunta|en=Faculty of Science|
dc.contributor.organizationfi=ohjelmistotekniikka|en=Software Engineering|
dc.contributor.organizationfi=sulautettu elektroniikka|en=Embedded Electronics|
dc.contributor.organization-code1.2.246.10.2458963.20.20754768032
dc.contributor.organization-code1.2.246.10.2458963.20.36798383026
dc.contributor.organization-code2606804
dc.converis.publication-id2913604
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/2913604
dc.date.accessioned2022-10-28T14:26:24Z
dc.date.available2022-10-28T14:26:24Z
dc.description.abstract<p> Facial expression recognition has broad application prospects in the fields of psychological study, nursing care, Human Computer Interaction as well as affective computing. The method with surface Electromyogram (sEMG), which is one of vital bio-signals, has its superiority in several aspects such as high temporal resolution and data processing efficiency over other methods. Researches regarding EMG signal to study emotional expression have started since the second half of last century. Meanwhile, studies on myoelectrical control systems focusing on the computation of bio-signal processing and data analysis have been blooming in the recent twenty years. To have a comprehensive view of utilizing facial sEMG method, a systematic review is presented in this paper for facial expression recognition from experiment design to measurement systems, and data analysis steps.</p>
dc.format.pagerange981
dc.format.pagerange988
dc.identifier.isbn978-1-5090-0153-8
dc.identifier.olddbid188274
dc.identifier.oldhandle10024/171368
dc.identifier.urihttps://www.utupub.fi/handle/11111/43637
dc.identifier.urnURN:NBN:fi-fe2021042714910
dc.language.isoen
dc.okm.affiliatedauthorJiang, Mingzhe
dc.okm.affiliatedauthorRahmani, Amir
dc.okm.affiliatedauthorWesterlund, Tomi
dc.okm.affiliatedauthorLiljeberg, Pasi
dc.okm.affiliatedauthorTenhunen, Hannu
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.conferenceIEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing
dc.relation.doi10.1109/CIT/IUCC/DASC/PICOM.2015.148
dc.source.identifierhttps://www.utupub.fi/handle/10024/171368
dc.titleFacial expression recognition with sEMG method
dc.title.book2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM)
dc.year.issued2015

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