中文摘要：

针对实际采集的脑电信号受眼电干扰较大,提出一种基于离散小波变换（DWT）与独立分量分析（ICA）的自动去除眼电伪迹的方法（DWIC）.对采集的多导脑电和眼电信号进行离散小波变换,获取多尺度小波系数,将串接小波系数作为ICA的输入;利用基于负熵判据的FastICA算法实现独立成分的快速获取,引入夹角余弦准则自动识别眼迹成分,并经过ICA逆变换将剔除眼迹后的独立成分投影返回到原脑电信号各个电极;通过DWT逆变换重构信号,即可得到去除眼迹的各导脑电信号.实验结果表明,DWICA方法极大地提高了脑电信号的信噪比,抗噪能力强且实时性好,为脑电信号的在线预处理提供了新思路.

英文摘要：

Electroencephalography（EEG）is easily affected by ocular artifact（OA）,which appears in EEG randomly as a big pulse.Based on discrete wavelet transform（DWT）and independent component analysis（ICA）,a novel automatic method of OA removal, denoted as DWICA,was proposed.Firstly,DWT was applied to the recorded EEG and electrooculogram（EOG） to obtain multiple scale coefficients,and the combined coefficients were considered as the input for ICA.Secondly,the independent components were acquired based on FastICA algorithm with negentropy criterion.The angle cosine criterion was introduced to recognize ocular artifact component.Furthermore,the inverse algorithm of ICA was applied to project the independent components without OA to original electrodes.Finally,the EEG were reconstructed using the inverse algorithm of DWT,and then the pure EEG were obtained. Experimental results show that DWICA is preferable in automatic removal of OA.The method provides a new idea for online preprocessing of EEG signals.