Method for detecting music to match the user's mood in prefrontal cortex electroencephalogram activity based on individual characteristics

Shin Ichi Ito, Yasue Mitsukura, Minoru Fukumi, Jianting Cao

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

2 Citations (Scopus)

Abstract

In this paper, we propose a method for detecting the music to match a user's mood in prefrontal cortex electroencephalogram (EEG) activity. The EEG frequencies analyzed are the components that contain significant and immaterial information. We focused on the combinations of the significant frequency. These frequency combinations are thought to express individual characteristics of EEG activity. In the proposed method, we calculate the percentage of the spectrum of these frequency combinations that does not include the noise frequency components and evaluates whether the music matches the user's mood through a simple threshold processing. Then, a genetic algorithm (GA) is used to specify the frequency of individual characteristics on the EEG. Threshold values that used the threshold processing is determined in the GA. Finally, the performance of the proposed method is evaluated using real EEG data.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Pages2640-2644
Number of pages5
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
Duration: 2007 Oct 72007 Oct 10

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Other

Other2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Country/TerritoryCanada
CityMontreal, QC
Period07/10/707/10/10

ASJC Scopus subject areas

  • Engineering(all)

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