Recently in the world, the research of the electroencephalogram (EEG) interface is done, because it has the possibility to realize an interface that can be operated without special knowledge and technology by using the EEG as a means of the interface. As one of the EEG interface, as for a goal for the final of this research, the EEG control system by any music is constructed. However, the EEG control by music is very difficult because it does not know the music and the causal relation of the EEG clearly. Therefore, the EEG analysis and music analysis is absolutely imperative in this system. In this paper, the EEG analysis method by using the FA and the NN is proposed. The FA is used for extracting the characteristics data of the EEG. The NN is used for estimating extracted the characteristics data of the EEG. Moreover teacher signal data of the NN uses the data of the characteristics data of the music. The characteristics data of music is extracted by using the Bark scale analysis. Finally, in order to show the effectiveness of the proposed method, classifying the EEG pattern is done computer simulations. The EEG pattern is 4 conditions, which are listening to Rock music, Schmaltzy Japanese ballad music, Healing music, and Classical music.
|出版ステータス||Published - 2003 9月 24|
|イベント||International Joint Conference on Neural Networks 2003 - Portland, OR, United States|
継続期間: 2003 7月 20 → 2003 7月 24
|Other||International Joint Conference on Neural Networks 2003|
|Period||03/7/20 → 03/7/24|
ASJC Scopus subject areas