Feature extraction in listening to music using statistical analysis of the EEG

Takahiro Ogawa, Stephen Karungaru, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

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

6 Citations (Scopus)

Abstract

In order to solve stress problems, researchers have studied healing, especially the music therapy. It is mentioned that objective evaluation of the music therapy is an important assignment, and some researchers have tried objective measurement based on physiological change. In this paper, the purpose is extraction of features that may be influenced by the music. We pay attention to EEG (electroencephalogram) as an objective and absolute scale. This paper proposes a method that extracts features of the EEG by the CDA(canonical discriminant analysis. From the result of the experiment, it is suggested that the CDA extracts the features influenced by the individual and the music type.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages5120-5123
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Publication series

Name2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

Keywords

  • Music therapy
  • The EEG
  • The canonical variate analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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