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dc.contributor.authorOzel, Pinar
dc.contributor.authorAkan, Aydin
dc.contributor.authorYilmaz, Bulent
dc.date.accessioned2021-08-23T08:15:20Z
dc.date.available2021-08-23T08:15:20Z
dc.date.issued2017en_US
dc.identifier.isbn978-1-5386-0633-9
dc.identifier.urihttps://hdl.handle.net/20.500.12573/926
dc.description.abstractIn recent years, wavelet-based, Fourier-based and Hilbert-based time-frequency methods attracted attention in emotion state classification studies in human machine interaction. In particular, the Hilbert-based Empirical Mode Decomposition and Wavelet-based Discrete Wavelet Transform have found applications in emotional state analysis. In this study, a model of emotional elicitation is proposed in which the classification is made by using the features of the wavelet coefficients obtained after applying the Discrete Wavelet Transform to IMFs achieved by using Multivariate Empirical Mode Decomposition. Accordingly, EEG data available in the DEAP database were classified as low / high for valence, activation, and dominance dimensions, and 4 different classifiers were used in the classification phase. The best ratios of valence, activation and dominance were obtained ideally 70.1%, 58.8%, 60.3% respectively.en_US
dc.description.sponsorshipIEEE Turkey Secten_US
dc.language.isoturen_US
dc.publisherIEEE345 E 47TH ST, NEW YORK, NY 10017 USAen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDiscrete Wavelet Transformen_US
dc.subjectMultivariate Empirical Mode Decompositionen_US
dc.subjectEEGen_US
dc.subjectEmotional State Analysisen_US
dc.titleEmotion Elicitation Analysis in Multi-Channel EEG Signals Using Multivariate Empirical Mode Decomposition and Discrete Wavelet Transformen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentAGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümüen_US
dc.contributor.institutionauthorYilmaz, Bulent
dc.relation.journalMedical Technologies National Congress (TIPTEKNO)en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US


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