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dc.contributor.authorLin, Yuan-Pinen_US
dc.contributor.authorChen, Jyh-Horngen_US
dc.contributor.authorDuann, Jeng-Renen_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorJung, Tzyy-Pingen_US
dc.date.accessioned2014-12-08T15:21:44Z-
dc.date.available2014-12-08T15:21:44Z-
dc.date.issued2011en_US
dc.identifier.isbn978-1-4244-4122-8en_US
dc.identifier.urihttp://hdl.handle.net/11536/15457-
dc.description.abstractElectroencephalogram (EEG)-based emotion recognition has been an intensely growing field. Yet, how to achieve acceptable accuracy on a practical system with as fewer electrodes as possible is less concerned. This study evaluates a set of subject-independent features, based on differential power asymmetry of symmetric electrode pairs [1], with emphasis on its applicability to subject variability in music-induced emotion classification problem. Results of this study have evidently validated the feasibility of using subject-independent EEG features to classify four emotional states with acceptable accuracy in second-scale temporal resolution. These features could be generalized across subjects to detect emotion induced by music excerpts not limited to the music database that was used to derive the emotion-specific features.en_US
dc.language.isoen_USen_US
dc.titleGeneralizations of the Subject-independent Feature Set for Music-induced Emotion Recognitionen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)en_US
dc.citation.spage6092en_US
dc.citation.epage6095en_US
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000298810004252-
Appears in Collections:Conferences Paper