Presentation 2004/6/18
Feature Extraction of EEG Patterns in Music Listening
Takahiro Ogawa, Yasue MITSUURA, Minoru FUKUMI, Norio AKAMATSU,
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Abstract(in English) Recentry, various illnesses are caused by stress, and stress release is being carried out by music therapy. Music used in the music therapy is various, and it takes a long times for patient and music therapist to select the music. Generally time selecting a music will be reduced and the music therapy can be done more easily if an effective music for it is found. In this paper, we measure EEC and extract EEC difference between music genres as characteristic data. Our method makes data based on frequency appearance ratio, extract features by principal conponent analysis, and then analyze them by using a neural network. Finally the effectiveness of our method is demonstrated by means of computer simulations.
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Keyword(in English) Music therapy / EEG / Principal component analysis / Neural network
Paper # NC2004-42
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Committee NC
Conference Date 2004/6/18(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Feature Extraction of EEG Patterns in Music Listening
Sub Title (in English)
Keyword(1) Music therapy
Keyword(2) EEG
Keyword(3) Principal component analysis
Keyword(4) Neural network
1st Author's Name Takahiro Ogawa
1st Author's Affiliation University of Tokushima()
2nd Author's Name Yasue MITSUURA
2nd Author's Affiliation Okayama University
3rd Author's Name Minoru FUKUMI
3rd Author's Affiliation University of Tokushima
4th Author's Name Norio AKAMATSU
4th Author's Affiliation University of Tokushima
Date 2004/6/18
Paper # NC2004-42
Volume (vol) vol.104
Number (no) 140
Page pp.pp.-
#Pages 5
Date of Issue