• DocumentCode
    1610181
  • Title

    Feature Extraction in Listen´ng to Music Using Statistical Analystis of the EEG

  • Author

    Ogawa, Takahiro ; Karungaru, Stephen ; Mitsukura, Yasue ; Fukumi, Minoru ; Akamatsu, N.

  • Author_Institution
    Tokushima Univ.
  • fYear
    2006
  • Firstpage
    5120
  • Lastpage
    5123
  • 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
  • Keywords
    electroencephalography; feature extraction; medical signal processing; music; patient treatment; statistical analysis; EEG; canonical discriminant analysis; electroencephalogram; feature extraction; music therapy; physiological change; statistical analysis; stress problems; Agriculture; Electroencephalography; Fatigue; Feature extraction; Frequency; Human factors; Medical treatment; Pain; Performance evaluation; Stress; music therapy; the EEG; the canonical variate analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE-ICASE, 2006. International Joint Conference
  • Conference_Location
    Busan
  • Print_ISBN
    89-950038-4-7
  • Electronic_ISBN
    89-950038-5-5
  • Type

    conf

  • DOI
    10.1109/SICE.2006.315382
  • Filename
    4108692