【摘要】 先简要介绍了独立分量分析的基本思想及算法,再将其应用于脑电信号的消噪和思维脑电的特征提取两个方面。实验结果表明:ICA可以将脑电信号中包含的心电(ECG)、眼电(EOG)等多种干扰信号成功地分离出来。另外,通过使用ICA方法对进行不同心理作业的脑电信号进行分析处理后,发现了与心理作业相对应的脑电独立分量特征,这些稳定的独立分量特征将可以为心理作业的分类和脑-机接口技术(BCI)提供新的实现方法.更多还原

【Abstract】 Recently, blind source separation (BSS) by ICA has received attention because of its potential application in many signal processing fields. In this paper, ICA is applied to the EEG signal analysis. One side, our results show that ICA can effectively detect, separate and remove a wide variety of artifacts from EEG recordings. On the other, the ICA algorithm is used to the pattern extraction of mental EEG signals from different mental tasks. By studying the EEG independent sources and their projection on human scalp, we can find that some steady independent components always appear when the subject repeats the same mental tasks. This result will provide us with a promising method in the classification of mental tasks and the research on the Brain-Computer Interface (BCI) technology.更多还原