Feature extraction from EEG patterns in music listening

Takahiro Ogawa, Shin Ichi Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsua

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Recently, various illnesses are caused by stress, and stress release is being carried out by musical therapy. Music used in the musical therapy is various, and it takes a long time for patient and music therapist to select the music. Generally, time selecting music can be reduced and the musical therapy can be done more easily if music effective for it is easily found. For this purpose, we measure and extract an EEC (electroen-cephalogram) difference between music genres as characteristic data in this paper. Our method makes data based on frequency appearance rate, extract features by the principal component analysis, and then analyze them by using a neural network. Finally in order to show the effectiveness of the proposed method, we carried out computer simulations by using the real data.

Original languageEnglish
Title of host publicationProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
EditorsS.J. Ko
Pages17-21
Number of pages5
Publication statusPublished - 2004 Dec 1
Externally publishedYes
EventProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004 - Seoul, Korea, Republic of
Duration: 2004 Nov 182004 Nov 19

Publication series

NameProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004

Other

OtherProceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2004
Country/TerritoryKorea, Republic of
CitySeoul
Period04/11/1804/11/19

ASJC Scopus subject areas

  • Engineering(all)

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