In:
Clinical EEG and Neuroscience, SAGE Publications, Vol. 43, No. 1 ( 2012-01), p. 32-38
Abstract:
This study proposed a recognized system for electroencephalogram (EEG) data classification. In addition to the wavelet-based amplitude modulation (AM) features, the fuzzy c-means (FCM) clustering is used for the discriminant of left finger lifting and resting. The features are extracted from discrete wavelet transform (DWT) data with the AM method. The FCM is then applied to recognize extracted features. Compared with band power features, k-means clustering, and linear discriminant analysis (LDA) classifier, the results indicate that the proposed method is satisfactory in applications of brain–computer interface (BCI).
Type of Medium:
Online Resource
ISSN:
1550-0594
,
2169-5202
DOI:
10.1177/1550059411429528
Language:
English
Publisher:
SAGE Publications
Publication Date:
2012
detail.hit.zdb_id:
2647038-X
detail.hit.zdb_id:
2140201-2
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