用独立分量分析去除大鼠模型脑电信号中的心电干扰

ICA for Removal of ECG Interference Embedded in EEG Recording of Rat Experiment Model

为有效去除混杂在大鼠模型脑电信号θ,α波频率段内的心电干扰信号,本文基于大鼠模型脑电、心电信号源之间的相互独立性,提出采用独立分量分析技术分离出混杂在大鼠模型脑电信号中的心电干扰信号.采用美国NEURO SCAN公司脑电记录系统,同步采集大鼠模型脑电和心电信号.为了比较,分别采用独立分量分析和小波分析技术去除混杂在大鼠模型脑电信号,θα波频率段内的心电干扰信号,采用频谱分析验证上述方法去除心电干扰信号的效果.结果表明,与小波分析技术相比,独立分量分析技术能够更加有效去除混杂在大鼠模型脑电信号,θα波频率段内的心电干扰信号,保持大鼠模型脑电信号的有效频率成分不丢失,为进一步评价脑功能研究提供了可靠依据.

This study investigated the application of the independent component analysis （ICA） to remove electrocardiogram （ECG） interference embedded in the frequency bands θ and α waves of the electroencephalogram （EEG） recording of rat experiment model, based on the fact that there is the independence between ECG and EEG from rat. The EEG and ECG signals from rat experiment model were simultaneously acquired by using Neuroscan electroencephalogram recording system （USA）. For the comparison, the wavelet analysis and ICA were applied to remove the ECG interference signal embedded in the frequency bands θ and α waves of EEG recording of rat experiment model, respectively. The power spectra of EEG obtained by using above two analysis techniques were calculated to demonstrate the validity of artifact cancellation. The results show that the performance of ICA for removing the ECG embedded in the frequency bands θ and α waves of EEG recording is superior to that of the wavelet analysis, which will be beneficial to the study on the assessment of brain function in the future.