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A comparative study of machine learning techniques for emotion recognition using peripheral physiological signals

dc.contributor.authorVijayakumar, Sowmya
dc.contributor.authorFlynn, Ronan
dc.contributor.authorMurray, Niall
dc.date.accessioned2020-11-24T11:59:29Z
dc.date.available2020-11-24T11:59:29Z
dc.date.copyright2020
dc.date.issued2020-06
dc.identifier.citationVijayakumar, S., Flynn, R., Murray, N. (2020). A comparative study of machine learning techniques for emotion recognition using peripheral physiological signals. Presented at AIT Poster Presentation Seminar June 2020en_US
dc.identifier.urihttp://research.thea.ie/handle/20.500.12065/3497
dc.description.abstractEmotions in human produce physical and physiological changes. Recent developments in wearable technology have led to increased research interest in using peripheral physiological signals for emotion recognition Peripheral signals are non-invasive Easily measured through wearables Long-term monitoring Real-time prediction applicationsen_US
dc.formatPDFen_US
dc.language.isoengen_US
dc.publisherAthlone Institute of Technologyen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPeripheralen_US
dc.subjectPhysiological signalsen_US
dc.subjectEmotion recognitionen_US
dc.subjectMachine learningen_US
dc.subjectWearablesen_US
dc.subjectClassificationen_US
dc.titleA comparative study of machine learning techniques for emotion recognition using peripheral physiological signalsen_US
dc.typeinfo:eu-repo/semantics/otheren_US
dc.contributor.affiliationAthlone Institute of Technologyen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-7304-8342en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-6475-005Xen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-1364-5583en_US
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessen_US
dc.subject.departmentFaculty of Engineering & Informatics AITen_US
dc.type.versioninfo:eu-repo/semantics/publishedVersionen_US


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International