Judging Emotion from EEGs Based on an Association Mechanism | Zendy

Seiji Tsuchiya | Zendy; Mayo Morimoto | Zendy; Misako Imono | Zendy; Hirokazu Watabe | Zendy

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Judging Emotion from EEGs Based on an Association Mechanism

Author(s) -

Seiji Tsuchiya,

Mayo Morimoto,

Misako Imono,

Hirokazu Watabe

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.102

Subject(s) - association (psychology) , computer science , mechanism (biology) , electroencephalography , support vector machine , association rule learning , artificial intelligence , focus (optics) , natural language processing , cognitive psychology , psychology , psychotherapist , philosophy , epistemology , physics , psychiatry , optics

Authors focus on the emotion of which common sense and attempt to compose a method that judge the user's emotion, based on EEGs. Emotion is judged from EEG features by an Association Mechanism. The Association Mechanism consists of the Concept Base and the Degree of Association. The methods of a Concept Base and a Degree of Association were proposed in the field of the natural language processing. In this paper, the research results are applied to EEGs. As a result, accuracy of emotion judgment from EEGs using the Association Mechanism was 57.6%. As a comparison, accuracy of emotion judgment at random was 25.0%, and accuracy of emotion judgment using SVM was 43.6%

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