摘要
脑电信号中往往含有各种形式的噪声干扰信号。这些干扰成分包括眼电、心电伪迹以及工频干扰等。由于干扰信号和脑电信号在频域上相互重叠,因此用时域或频域滤波的方法难以有效地消除脑电信号中的干扰成分。独立分量分析(Independent Component Analysis,ICA)是20世纪90年代发展起来的一种新的盲源分离方法(Blind Source Separation,BSS),将ICA方法应用于实测脑电信号的处理,获得非常理想的消噪效果。
Severe contamination of EEG activity by eye movements, blinks and muscle, heart and power line noise presents a serious preblem for EEG interpretation and analysis. As the interferences and EEG are overlapped in frequency spectrum, so the traditional time or frequency method can not get good results to remove the artifacts and noise in EEG. Independent component analysis（ICA）is a new approach to blind source separation（BSS）developed in mid 90 of the 20^th century. ICA method was applied to real-life multi-channel EEG signals to remove the EOG artifacts and excellent result has been achieved.
出处
《现代制造工程》
CSCD
2006年第2期89-91,共3页
Modern Manufacturing Engineering
关键词
脑电
独立分量分析
眼电
EEG Independent component analysis EOG
