AUTOMATED AND ADAPTIVE FEATURE EXTRACTION FOR BRAIN-COMPUTER INTERFACES BY USING WAVELET PACKET

摘要：

An automated and adaptive feature extraction method is discussed in this paper. The method is based on the Wavelet Packet Transform (WPT) and used to extract features of electroencephalogram (EEG) signals for brain computer interfaces (BCIs). The idea is to employ the best basis algorithm to select the most appropriate wavelet and the best wavelet packet basis automatically. Meanwhile, both the selected wavelet and the selected basis are adaptive to each EEG channel and each subject. The effectiveness of the method is verified by discriminating three different motor imagery tasks of six subjects.

关键词： Brain-computer interface (BCI) Wavelet packet transform (WPT) Fuzzy sets Electroencephalogram (EEG)

作者: GUO-ZHENG YAN BANG-HUA YANG SHUO CHEN

作者单位: Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China Department of Psychology and Behavior Science, Zhejiang University, Hangzhou, 310028 China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 4248-4251

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）