近十几年来，脑机接口(BCI)技术的研究在国际上引起来广泛的研究兴趣并获得了快速的发展。它可以为神经肌肉损伤患者提供一种不依赖正常的外围神经和肌肉输出通道的新的通讯工具，也可以为正常人提供辅助控制通道或在特殊环境下的控制通道，因此具有巨大的社会价值和应用前景。 信号分析与处理环节是实现BCI系统、提高系统可靠性与性能的关键，也是本文研究的主要内容。本文结合国际BCI竞赛Ⅲ提供的数据，运用多种方法进行分析对比，对脑电(EEG)数据的特点获得了感性认识。然后运用基于公共空域模式(CSP)分析方法，对左右手指动作的多通道脑电信号进行 了空间滤波，提取出想象左右手运动过程中的特异性成份;最后，根据提取的特征进行了手指动作的识别。试验结果表明 CSP 方法能提取出不同运动方向的特异性成份，基于这些特异性成份设计的BCI系统具有较好的识别率。

1。Over the past decade, there has been great interest and a rapid development in the research of Brain-Computer Interface technology.BCI can provide a new communication option that does not depend on peripheral nerves and muscles for those with neuromuscular impairments, and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances. Signal analysis and processing is a key issue for implementation of a BCI system as well as improving its reliability and performance, and which is the main contents of this paper. This paper deals with the EEG data provided by BCI Competition, analyzing them by various methods, acquiring some perceptual perception of EEG, and then complete the feature extraction of multi-channel two-class EEG data of finger motor imaginary. At last, according to the feature extracted some testing data was classified; with a result declaring that CSP algorithm can extract specificity components of two-direction motor imaginary.In addition, BCI systems designed based on those specificity components give a fine discrimination.