Feature extraction from EEG patterns in music listening

Takahiro Ogawa, Shin Ichi Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsua

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

Recently, various illnesses are caused by stress, and stress release is being carried out by musical therapy. Music used in the musical therapy is various, and it takes a long time for patient and music therapist to select the music. Generally, time selecting music can be reduced and the musical therapy can be done more easily if music effective for it is easily found. For this purpose, we measure and extract an EEC (electroen-cephalogram) difference between music genres as characteristic data in this paper. Our method makes data based on frequency appearance rate, extract features by the principal component analysis, and then analyze them by using a neural network. Finally in order to show the effectiveness of the proposed method, we carried out computer simulations by using the real data.

本文言語English
ホスト出版物のタイトルProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
編集者S.J. Ko
ページ17-21
ページ数5
出版ステータスPublished - 2004 12 1
外部発表はい
イベントProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004 - Seoul, Korea, Republic of
継続期間: 2004 11 182004 11 19

出版物シリーズ

名前Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004

Other

OtherProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
国/地域Korea, Republic of
CitySeoul
Period04/11/1804/11/19

ASJC Scopus subject areas

  • 工学(全般)

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