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ID 112404
著者
藤澤, 正一郎 The University of Tokushima KAKEN研究者をさがす
キーワード
electroencephalogram
matching patterns
personality
egogram
Yatabe-Guilford personality inventory
Kretschmer type personality inventory
k - nearest neighbour method
資料タイプ
学術雑誌論文
抄録
In this paper we introduce a method to classify matching patterns between music and human mood using an electroencephalogram (EEG) analysis technique and considering personality. We analyse the EEG of the left prefrontal cortex by single-point sensing. The EEG recording device uses dry-type sensors. The feature vector is created by connecting the personality quantification results and the EEG features. Egograms—the Yatabe-Guilford personality inventory and a Kretschmer-type personality inventory are used to quantify personality. The EEG features are extracted using fast Fourier transform. Then, the matching patterns are classified using the k -nearest neighbour method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data.
掲載誌名
The Online Journal on Computer Science and Information Technology
ISSN
20904517
出版者
International Foundation for Modern Education and Scientific Research
5
3
開始ページ
341
終了ページ
345
発行日
2015-07
権利情報
This work is licenced under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.(CC BY NC-ND)
EDB ID
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
理工学系