An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform

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dc.contributor.affiliationGómez, A., Mathematical Modeling Research Group, GRIMMAT, Universidad EAFIT, Medellín, Colombiaspa
dc.contributor.affiliationMedical Technology Laboratory, GATEME, Universidad Nacional de San Juan, San Juan, Argentinaspa
dc.contributor.affiliationPsychology, Education and Culture Research Group, Institución Universitaria Politécnico Grancolombiano, Bogotá, Colombiaspa
dc.contributor.affiliationSystem Engineering Research Group, ARKADIUS, Universidad de Medellín, Medellín, Colombiaspa
dc.contributor.affiliationFunctional Analysis and Aplications Research Group, Universidad EAFIT, Medellín, Colombiaspa
dc.contributor.affiliationMejía, G., Functional Analysis and Aplications Research Group, Universidad EAFIT, Medellín, Colombiaspa
dc.contributor.authorGómez A.
dc.contributor.authorQuintero L.
dc.contributor.authorLópez N.
dc.contributor.authorCastro J.
dc.contributor.authorVilla L.
dc.contributor.authorMejía G.
dc.date.accessioned2017-12-19T19:36:50Z
dc.date.available2017-12-19T19:36:50Z
dc.date.issued2017
dc.description.abstractIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.eng
dc.identifier.doi10.1007/978-981-10-4086-3_164
dc.identifier.instnameinstname:Universidad de Medellínspa
dc.identifier.isbn9789811040856
dc.identifier.issn16800737
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.urihttp://hdl.handle.net/11407/4354
dc.language.isoeng
dc.publisherSpringer Verlagspa
dc.publisher.facultyFacultad de Ingenieríasspa
dc.relation.ispartofIFMBE Proceedingsspa
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85018372191&doi=10.1007%2f978-981-10-4086-3_164&partnerID=40&md5=2ff10283d5e0d903cdc3699c25094a24
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dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceScopusspa
dc.subject.proposalEEGeng
dc.subject.proposalEmotioneng
dc.subject.proposalFeatureseng
dc.subject.proposalKNNeng
dc.subject.proposalQDAeng
dc.subject.proposalRFCeng
dc.subject.proposalWaveleteng
dc.subject.proposalBiomedical engineeringeng
dc.subject.proposalElectroencephalographyeng
dc.subject.proposalElectrophysiologyeng
dc.subject.proposalSignal processingeng
dc.subject.proposalSpeech recognitioneng
dc.subject.proposalDevelopmental psychologyeng
dc.subject.proposalEmotioneng
dc.subject.proposalEmotion recognitioneng
dc.subject.proposalEmotional stateeng
dc.subject.proposalFeatureseng
dc.subject.proposalSingle channel eegeng
dc.subject.proposalSingle-channel signalseng
dc.subject.proposalWaveleteng
dc.subject.proposalBiomedical signal processingeng
dc.titleAn approach to emotion recognition in single-channel EEG signals using stationarywavelet transformspa
dc.typeConference Paper
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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