Channel Selection for Motor Imagery-Based BCIs: A Semi-supervised SVM Algorithm

摘要：

Given a frequency band, we propose a semi-supervised SVM algorithm to select a set of channels for motor imagery-based BCIs in this paper. Both training data with labels and test data without labels are used for training a classifier in this approach. Hence, it is suitable for the case of small training data set. To test our algorithm, it is applied to a BCI competition data set. Data analysis results demonstrate the effectiveness of our algorithm.

关键词： Electroencephalogram (EEG) Motor imagery Brain computer interface (BCI) Channels Semi-supervised learning

作者: Jinyi Long Yuanqing Li Zhenghui Gu

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

会议类型: 国际会议

会议名称: The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)

会议地点: 杭州

会议语种:英文

页码: 701-708

在线出版日期: 2009-11-15（万方平台首次上网日期，不代表论文的发表时间）