摘要
运动想象脑电信号是指想象肢体运动而没有实际的肢体动作所产生的脑电信号。信号处理和模式分类方法是运动想象脑电信号以及整个BCl系统的核心技术。本文对基于运动想象的脑电信号的识别算法进行了综述。阐述了运动想象脑电特征提取和分类的方法,比较了各种方法的特点,分析了几种典型的特征提取和识别算法的组合,并且总结了运动想象脑电信号的特征提取和分类的发展现状和前景。
Motor imagery electroencephalogram （EEG）is produced by imaging limb movements without actual action. Signal processing and pattern classification are the key technologies of motor imagery EEG and the BCI system. The recognition algorithm based on motor imagery EEG is overviewed in this paper. Various methods for feature extraction and classification of motor imagery EEG are presented with their advantages and disadvantages. Combinations of typical algorithms for feature extraction and recognition are listed and analyzed. The present situation and prospect of feature extraction and classification of motor imagery EEG are summarized.
出处
《北京生物医学工程》
2013年第2期209-214,共6页
Beijing Biomedical Engineering
基金
国家自然科学基金(61003175/F020504)
中国博士后科学基金(20080441121)
辽宁省自然科学基金(20112015)资助
关键词
脑机接口
运动想象脑电信号
特征提取
分类器
brain computer interface
motor imagery electroencephalogram
feature extraction
classifier
