摘要
为消除脑电信号中的心电、眼电等伪差,在已有的不动点算法和带参考信号的独立分量分析算法的基础上,提出了一种多参考信号的独立分量分析方法.该方法通过计算各伪差在各路观测信号中的比重,去除伪差对观测信号的影响,从而得到较为纯净的脑电信号.所提方法相对于传统的fast ICA算法具有更小的计算量,并且不需要对分离的独立源进行人工干预,同时也是对ICA-R算法的一种扩展,解决了其只能提取单路源信号的缺点.仿真实验证明该方法更切合实际情况,而且能够更加有效地去除脑电信号中的多个伪差.
In order to eliminate the effect of artifacts in electroencephalograph （EEG） signals, such as electrocardiogram （ECG） and electrooculogram （EOG）, etc. , a new ICA （independent component analysis） method with multi-references is proposed based on the fixed-point algorithm and the ICA algorithm with references. After the proportions of artifacts in observation signals are calculated respectively, the comparatively pure EEGs are separated from the artifacts. Compared with fast ICA, the new method has less computational complexity and doesnrt need to dispose the independent sources. In addition, it can overcome the defect of ICA-R algorithm which just extracts single signal. Computer simulation demonstrates that the new method can effectively remove several artifacts from brain signals.
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2008年第5期740-743,共4页
Journal of Dalian University of Technology
基金
国家自然科学基金资助项目(30574075
30170259
60372081)
教育部博士学科点专项科研基金资助项目(20010141025)
关键词
独立分量分析
参考信号
伪差去除
脑电信号
independent component analysis （ICA）
reference signals
artifacts removing
electroencephalograph （EEG） signal
