标题:Bhattacharyya distance and confidence map based feature selection for Common spatial patterns algorithms in brain computer interface
作者:Sun, Hongyu ;Bi, Lijun ;Fan, Binghui ;Chen, Bisheng ;Guo, Yinjing
作者机构:[Sun, Hongyu ;Bi, Lijun ;Fan, Binghui ;Chen, Bisheng ;Guo, Yinjing ] College of Electronic Communication and Physics, Shandong University of Science a 更多
会议名称:12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015
会议日期:August 15, 2015 - August 17, 2015
来源:2015 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015
出版年:2015
页码:1537-1542
DOI:10.1109/FSKD.2015.7382173
摘要:A novel feature selection methodology based on Bhattacharyya distance and confidence map is presented and illustrated with electroencephalogram (EEG) signal classification problem. Although Common spatial pattern (CSP) is a mostly used algorithm for classification of EEG in brain-computer interface (BCI), which has poor frequency selectivity. To address this problem, a constant-bandwidth Butterworth filters bank was utilized for frequency decomposition. Then, our novel feature selection methodology was used for new CSP features ranking and selection. We compare our method with the existing approaches, the results on 4 subjects showed that the new method outperforms the other two existing approaches based on conventional CSP and Common Spatio-Spectral Pattern (CSSP), the proposed algorithm yielded lowest test error rate of 2.2±1.8% in subject 1 and will be a up-and-coming signal processing tool for developing BCI and improving the efficiency of the classification method in low-resolution EEG input and small-dataset conditions.
© 2015 IEEE.
收录类别:EI
资源类型:会议论文
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