The EEG feature extraction using the principal component analysis

Satomi Ota, Shin Ichi Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

研究成果: Paper査読


The diseases based on the stress are increasing in recent years. As one of the way deal with these diseases, music therapy is used. An effective on the music for music therapy is depended on a person. Therefore, it is important to select the music suitable for a person. In this paper, a system automatically selects the suitable music for music therapy from a large database of music by each EEG. By using this system, music therapy is done regardless of time and place, and it is needed for constructing this system to clear relations between the music and the EEG. In this paper, we measure the EEG of subjects in listening to music and extract some features of their patterns by using the Principal Component Analysis (PCA). Then we analyze them by using the neural networks (NN). Finally, in order to demonstrate the effective of the proposed method, we carry out the computer simulation. Then, we show the effectiveness of the proposed method.

出版ステータスPublished - 2005
イベントSICE Annual Conference 2005 - Okayama, Japan
継続期間: 2005 8月 82005 8月 10


OtherSICE Annual Conference 2005

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学


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