Bhattacharyya bound based channel selection for classification of motor imageries in EEG signals

@article{He2009BhattacharyyaBB,
  title={Bhattacharyya bound based channel selection for classification of motor imageries in EEG signals},
  author={Lin He and Zhu Liang Yu and Zhenghui Gu and Yuanqing Li},
  journal={2009 Chinese Control and Decision Conference},
  year={2009},
  pages={2353-2356}
}
In EEG-based brain computer interfaces (BCIs), channel selection is important for the classification of mental task, such as motor imagery. In this paper, a channel selection method is presented for motor imagery. The Bhattacharyya bound of common spatial pattern (CSP) features is used as the optimal index, and a fast sequential forward search is applied to find the optimal combination of channels. The data analysis results show the improvement of classification accuracy. 
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Chinese Control and Decision Conference (CCDC

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