Bhattacharyya Bound Based Channel Selection for Classification of Motor Imageries in EEG Signals

摘要：

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.

关键词： EEG Bhattacharyya Bound Common Spatial Pattern Sequential Forward Search Motor Imagery

作者: Lin He Zhuliang Yu Zhenghui Gu Yuanqing Li

作者单位: College of Automation Science and Technology, South China University of Technology, Guangzhou 510640

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 2353-2356

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）