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 Japanese) | (See Japanese page) |
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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Music therapy / EEG / Principal component analysis / Neural network |
Paper # | NC2004-42 |
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Committee | NC |
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Conference Date | 2004/6/18(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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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 |
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