Extraction of EEG characteristics while listening to music and its evaluation based on a latency structure model with individual characteristics

Shin Ichi Ito, Yasue Mitsukura, Hiroko Nakamura Miyamura, Takafumi Saito, Minoru Fukumi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

EEG is characterized by unique and individual characteristics. Little research has been done to take into account the individual characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. Then there is the difference of importance between the analyzed frequency components of the EEG. We think that the importance difference shows the individual characteristics. In this paper, we propose a new EEG extraction method of characteristic vector by a latency structure model in individual characteristics (LSMIC). The LSMIC is the latency structure model, which has personal error as the individual characteristics, based on normal distribution. The realcoded genetic algorithms (RGA) are used for specifying the personal error that is unknown parameter. Moreover we propose an objective estimation method that plots the EEG characteristic vector on a visualization space. Finally, the performance of the proposed method is evaluated using a realistic simulation and applied to real EEG data. The result of our experiment shows the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)9-17
Number of pages9
JournalElectronics and Communications in Japan
Volume92
Issue number1
DOIs
Publication statusPublished - 2009 Jan
Externally publishedYes

Fingerprint

electroencephalography
music
Model structures
Electroencephalography
Music
Latency
evaluation
Evaluation
Model
method of characteristics
Normal distribution
Method of Characteristics
Electroencephalogram
normal density functions
genetic algorithms
Unknown Parameters
Visualization
Gaussian distribution
Genetic algorithms
plots

Keywords

  • Electroencephalogram
  • Iatency structure model
  • Individual characteristics
  • Real-coded genetic algorithm
  • Visualization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Physics and Astronomy(all)
  • Signal Processing
  • Applied Mathematics

Cite this

Extraction of EEG characteristics while listening to music and its evaluation based on a latency structure model with individual characteristics. / Ito, Shin Ichi; Mitsukura, Yasue; Miyamura, Hiroko Nakamura; Saito, Takafumi; Fukumi, Minoru.

In: Electronics and Communications in Japan, Vol. 92, No. 1, 01.2009, p. 9-17.

Research output: Contribution to journalArticle

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