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

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

doi:10.1109/SICE.2006.315382

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 proceeding › Conference contribution

7 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 language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	5120-5123
Number of pages	4
DOIs	https://doi.org/10.1109/SICE.2006.315382
Publication status	Published - 2006 Dec 1
Externally published	Yes
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: 2006 Oct 18 → 2006 Oct 21

Publication series

Name	2006 SICE-ICASE International Joint Conference

Other

Other	2006 SICE-ICASE International Joint Conference
Country/Territory	Korea, Republic of
City	Busan
Period	06/10/18 → 06/10/21

Keywords

Music therapy
The EEG
The canonical variate analysis

ASJC Scopus subject areas

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2006.315382

Cite this

Ogawa, T, Karungaru, S, Mitsukura, Y, Fukumi, M & Akamatsu, N 2006, Feature extraction in listening to music using statistical analysis of the EEG. in 2006 SICE-ICASE International Joint Conference., 4108692, 2006 SICE-ICASE International Joint Conference, pp. 5120-5123, 2006 SICE-ICASE International Joint Conference, Busan, Korea, Republic of, 06/10/18. https://doi.org/10.1109/SICE.2006.315382

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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.",

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author = "Takahiro Ogawa and Stephen Karungaru and Yasue Mitsukura and Minoru Fukumi and Norio Akamatsu",

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AU - Ogawa, Takahiro

AU - Karungaru, Stephen

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

AU - Akamatsu, Norio

PY - 2006/12/1

Y1 - 2006/12/1

N2 - 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.

AB - 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.

KW - Music therapy

KW - The EEG

KW - The canonical variate analysis

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

Abstract

Publication series

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Keywords

ASJC Scopus subject areas

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