Classifying EEG for Brain-Computer Interface Using Spatio-Temporal Filters
Brain computer interface (BCI) is a new device which provides user a communication system between the brain and the external devices. EEGs recorded from scalp were analyzed in order to identify the humans intentions. The feature extraction of EEG signals plays an important role for classifying these spontaneous mental activities. In this paper, three subjects participated in the BCI experiment which contains three mental tasks including imagination of left hand, right hand and foot movement.After preprocessing, Spatio-temporal filters were applied to extract the feature of EEG signals. Then, Linear discriminant analysis (LDA) was used to classify the feature extracted. After that, a comparison of feature extract methods between Spatio-temporal filters and band power (BP) was made. The results show that it can be used as an effective method for classifying three different motor imaginations by Spatio-temporal filters.
Jiang Wang Guizhi Xu Lei Wang Huiyuan Zhang
Tangshan Vocational Technical College, Tangshan, Hebei Province, China Province-Ministry Joint Key L Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Tangshan Vocational Technical College, Tangshan, Hebei Province, China, 063000
国际会议
武汉
英文
184-187
2008-12-19（万方平台首次上网日期，不代表论文的发表时间）