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 12月 1|
|イベント||SICE Annual Conference 2005 - Okayama, Japan|
継続期間: 2005 8月 8 → 2005 8月 10
|Other||SICE Annual Conference 2005|
|Period||05/8/8 → 05/8/10|
ASJC Scopus subject areas
- コンピュータ サイエンスの応用