基于独立分量分析的心理作业诱发脑电特征增强  

Pattern enhancement of EEG evoked by mental tasks based on independent component analysis

作　　者：张磊[1] 张道信[1] 吴小培[1] 

机构地区：[1]安徽大学计算智能与信号处理教育部重点实验室,安徽合肥230039

出　　处：《安徽大学学报（自然科学版）》2008年第2期39-43,共5页Journal of Anhui University(Natural Science Edition)

基　　金：国家自然科学基金资助项目(60271024);安徽省自然科学基金资助项目(070412038)

摘　　要：作者采用独立分量分析(Independent Component Analysis)方法对心理作业诱发的脑电信号进行了分析.研究表明,ICA能有效地从多路头皮脑电中分离出脑电信号的基本节律成分.通过对脑电独立源谱特征和ICA混合矩阵分析,可得到基本节律成分在头皮电极的能量分布情况,进而揭示心理作业与脑电特征的关系.In this paper, independent component analysis was employed to EEG pattern enhancement of mental tasks. The experiment results showed that ICA can separate the basic rhythms from the multi -channel scalp EEG effectively. By analyzing the frequency spectrum of ICs and the mixing matrix estimated by ICA algorithm, the energy projection of basic rhythms on the scalp electrodes was achieved. Based on that, the relationship between the mental tasks and EEG pattern was studied.

关 键 词：独立分量分析 脑电 特征增强 

分 类 号：O441[理学—电磁学]