A self produced mother wavelet feature extraction method for motor imagery brain-computer interface

W. L. Yeh, Y. C. Huang, J. H. Chiou, J. R. Duann, J. C. Chiou

研究成果: 書貢獻/報告類型會議論文篇章同行評審

2 引文 斯高帕斯(Scopus)

摘要

Motor imagery base brain-computer interface (BCI) is an appropriate solution for stroke patient to rehabilitate and communicate with external world. For such applications speculating whether the subjects are doing motor imagery is our primary mission. So the problem turns into how to precisely classify the two tasks, motor imagery and idle state, by using the subjects' electroencephalographic (EEG) signals. Feature extraction is a factor that significantly affects the classification result. Based on the concept of Continuous Wavelet Transform, we proposed a wavelet-liked feature extraction method for motor imagery discrimination. And to compensate the problem that the feature varies between subjects, we use the subjects' own EEG signals as the mother wavelet. After determining the feature vector, we choose Bayes linear discriminant analysis (LDA) as our classifier. The BCI competition III dataset IVa is used to evaluate the classification performance. Comparing with variance and fast Fourier transform (FFT) methods in feature extraction, 2.02% and 16.96% improvement in classification accuracy are obtained in this work respectively.

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主出版物標題2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
頁面4302-4305
頁數4
DOIs
出版狀態已出版 - 2013
事件2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
持續時間: 3 7月 20137 7月 2013

出版系列

名字Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN(列印)1557-170X

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???event.eventtypes.event.conference???2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
國家/地區Japan
城市Osaka
期間3/07/137/07/13

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