常州大学学报（自然科学版）2013，Vol.25Issue(1)：25-30,6.DOI:10.3969/j.issn.2095-0411.2013.01.005
左右手运动想象脑电模式识别研究
Study of Discrimination between Left and Right Hand Movements Imagery Event-Related EEG Pattern
摘要
Abstract
Recently, accurate classification of imaginary left and right hand movemetns of EEG is an important issue in brainOcomputer interface (BCD. Based on EEG data of 3 subjects which collected by -American EGI 640 -channel EEG colletion system, firstly, the effective de-noising processing to collected data by the independent component analysis method is carried out. Secondly, discrete wavelet transform method is used to decompose the average power of the channel C3/C4 in left and right hand movements imagery. The reconstructed signal of approximation coefficient A6 on the sixth level is selected to build up feature signal. Finally, to classify the feature signal respectively by Fisher Linear Discriminant Analysis (FL-DA), Support Vector Machines (SVM) and Extreme Learning Machine (ELM) methods. The classification results show that the average classification rate of -ELM is higher than that of FLDA and SVM, which can achieve 92%. The running speed of ELM is also faster than the other two methods.关键词
脑机接口/特征提取/模式识别/运动想象Key words
brain-computer interface/ feature extraction/ motor imagery/ pattern classification分类
能源科技引用本文复制引用
刘成,何可人,周天彤,邹凌..左右手运动想象脑电模式识别研究[J].常州大学学报（自然科学版）,2013,25(1):25-30,6.基金项目
国家自然基金项目(61201096) （61201096）
常州市科技项目(CJ20110023,CM20123006) （CJ20110023,CM20123006）
