Feature extraction in listening to music using statistical analysis of the EEG

被引：0
|
作者：
Ogawa, Takahiro [1 ]
Karungaru, Stephen [1 ]
Mitsukura, Yasue [2 ]
Fukumi, Minoru [1 ]
Akamatsu, Norio [1 ]
机构：
[1] Univ Tokushima, 2-1 Minami Josanjima, Tokushima 7708506, Japan
[2] Tokyo Univ Agr & Technol, Koganei, Tokyo 1848588, Japan
来源：
2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13 | 2006年
关键词：
music therapy; the EEG; the canonical variate analysis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to solve stress problems, researchers have studied healing, especially the music therapy. It is mentioned that objective evaluation of the music therapy is an important assignment, and some researchers have tried objective measurement based on physiological change. In this paper, the purpose is extraction of features that may be influenced by the music. We pay attention to EEG (electroencephalogram) as an objective and absolute scale. This paper proposes a method that extracts features of the EEG by the CDA(canonical discriminant analysis. From the result of the experiment, it is suggested that the CDA extracts the features influenced by the individual and the music type.
引用
收藏
页码：3267 / +
页数：2
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