Investigation of methods for extracting features related to motor imagery and resting states in EEG-based BCI system

I. Putu Susila, Shin'Ichiro Kanoh, Koichiro Miyamoto, Tatsuo Yoshinobu

研究成果: Article査読

1 被引用数 (Scopus)

抄録

Methods for extracting features of motor imagery from 1-channel bipolar EEG were evaluated. The EEG power spectrums which were used as feature vectors were calculated with filter bank, FFT and AR model, and were then classified by linear discriminant analysis (LDA) to discriminate motor imagery and resting states. It was shown that the extraction method using AR model gave the best result with the average true positive rate of 83% (a -7%). Furthermore, when principal component analysis (PCA) was applied to the feature vectors, the dimension of the feature vectors could be reduced without decreasing accuracy of discrimination.

本文言語English
ページ(範囲)1828-1833
ページ数6
ジャーナルIEEJ Transactions on Electronics, Information and Systems
129
10
DOI
出版ステータスPublished - 2009 1 1

ASJC Scopus subject areas

  • 電子工学および電気工学

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