Common Spatial Pattern Ensemble Classifier and Its Application in Brain-Computer Interface |
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Authors: | Xu Lei Ping Yang Peng Xu Tie-Jun Liu De-Zhong Yao |
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Affiliation: | Key Laboratory for NeuroInformation of Ministry of Education,School of Life Science and Technology,University of Electronic Science and Technology of China,Chengdu,610054,China |
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Abstract: | Common spatial pattern (CSP) algorithm is a successful tool in feature estimate of brain-computer interface (BCI).However,CSP is sensitive to outlier and may result in poor outcomes since it is based on pooling the covariance matrices of trials.In this paper,we propose a simple yet effective approach,named common spatial pattern ensemble (CSPE) classifier,to improve CSP performance.Through division of recording channels,multiple CSP filters are constructed.By projection,log-operation,and subtraction on the original signal,an ensemble classifier,majority voting,is achieved and outlier contaminations are alleviated.Experiment results demonstrate that the proposed CSPE classifier is robust to various artifacts and can achieve an average accuracy of 83.02%. |
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Keywords: | Brain-computer interface channel selection classifier ensemble common spatial pattern |
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