Ubiquitous Affective Computing: A Review

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dc.contributor.authorAssabumrungrat, Rawinko
dc.contributor.authorSangnark, Soravittko
dc.contributor.authorCharoenpattarawut, Thananyako
dc.contributor.authorPolpakdee, Wipamasko
dc.contributor.authorSudhawiyangkul, Thapanunko
dc.contributor.authorBoonchieng, Ekkaratko
dc.contributor.authorWilaiprasitporn, Theerawitko
dc.date.accessioned2022-04-15T06:43:50Z-
dc.date.available2022-04-15T06:43:50Z-
dc.date.created2022-03-14-
dc.date.created2022-03-14-
dc.date.created2022-03-14-
dc.date.issued2022-02-
dc.identifier.citationIEEE SENSORS JOURNAL, v.22, no.3, pp.1867 - 1881-
dc.identifier.issn1530-437X-
dc.identifier.urihttp://hdl.handle.net/10203/294765-
dc.description.abstractThis review investigated research works on affective computing by using electrocardiogram (ECG) and electrodermal activity (EDA). The 27 related research papers, including 23 from IEEE Journals and 4 from other Q1 Journals in the last five years, were studied. The main goals have been to summarize common trends in this field in recent years as well as provide discussions and a big picture of how future research should be done. The content of this review covers the fundamental pipeline of affective computing research consisting of stimuli, intelligent affective computing, and sensor design and data processing. Additionally, we discuss future research directions and potential applications, including stress monitoring, music cognition, and robotics, where ECG and EDA will play a significant role with wearable devices. Therefore, this review serves as an information summary for everyone who is interested in affective computing and improving AI's understanding of human emotion.-
dc.languageEnglish-
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.titleUbiquitous Affective Computing: A Review-
dc.typeArticle-
dc.identifier.wosid000750206700008-
dc.identifier.scopusid2-s2.0-85122099853-
dc.type.rimsART-
dc.citation.volume22-
dc.citation.issue3-
dc.citation.beginningpage1867-
dc.citation.endingpage1881-
dc.citation.publicationnameIEEE SENSORS JOURNAL-
dc.identifier.doi10.1109/JSEN.2021.3138269-
dc.contributor.localauthorCharoenpattarawut, Thananya-
dc.contributor.nonIdAuthorAssabumrungrat, Rawin-
dc.contributor.nonIdAuthorSangnark, Soravitt-
dc.contributor.nonIdAuthorPolpakdee, Wipamas-
dc.contributor.nonIdAuthorSudhawiyangkul, Thapanun-
dc.contributor.nonIdAuthorBoonchieng, Ekkarat-
dc.contributor.nonIdAuthorWilaiprasitporn, Theerawit-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorElectrocardiography-
dc.subject.keywordAuthorAffective computing-
dc.subject.keywordAuthorSensors-
dc.subject.keywordAuthorElectrodes-
dc.subject.keywordAuthorInternet-
dc.subject.keywordAuthorElectroencephalography-
dc.subject.keywordAuthorWearable computers-
dc.subject.keywordAuthorAffective computing-
dc.subject.keywordAuthorelectrocardiogram (ECG)-
dc.subject.keywordAuthorelectrodermal activity (EDA)-
dc.subject.keywordAuthoremotion-
dc.subject.keywordAuthorwearable devices-
dc.subject.keywordPlusEMOTION RECOGNITION-
dc.subject.keywordPlusMUSIC-
dc.subject.keywordPlusRESPONSES-
dc.subject.keywordPlusFEATURES-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusLIFE-
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