Automated Selecting Subset of Channels Based on CSP in Motor Imagery Brain-Computer Interface System
The Common Spatial Pattern (CSP) algorithm is a popular method for efficiently calculating spatial filters. However, several previous studies show that CSPs performance deteriorates especially when the number of channels is large compared to small number of training datasets. As a result, it is necessary to choose an optimal subset of the whole channels to save computational time and retain high classification accuracy. In this paper, we propose a novel heuristic algorithm to select the optimal channels for CSP. The CSP procedure is applied to training datasets firstly and then a channel score based on 1 norm is defined for each channel. Finally, channels with larger scores are retained for further CSP processing. This approach utilizes CSP procedure twice to select channels and extract features, respectively; hence the complex optimization problem of channel selection for CSP is solved heuristically. We apply our method and other two existing methods to datasets from BCI competition 2005 for comparison and the experiment results show this method provides an effective way to accomplish the task of channel selection.
Jianjun Meng Guangquan Liu Gan Huang Xiangyang Zhu
Robotics Institute,School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,200240,China
国际会议
2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)
桂林
英文
2290-2294
2009-12-19（万方平台首次上网日期，不代表论文的发表时间）