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目的研究对混杂有眼电和心电干扰脑电信号的处理方法。方法首先用二代小波硬/软阈值、折衷阈值、μ律阈值方法对脑电信号消噪,然后运用FastICA算法对消噪后仍含眼电和心电的脑电信号进行盲信号分离。结果二代小波μ律阈值方法对脑电信号有较好的消噪效果,FastICA算法能成功分离出脑电中眼电和心电的干扰。结论运用二代小波μ律阈值法对脑电消噪后再用FastICA算法对独立源产生的干扰进行分离是一种有效的预处理方法。
Objective To study the method of processing EEG signals mixed with EEG and ECG. Methods Firstly, the second generation wavelet hard / soft threshold, trade-off threshold and μ-law threshold were used to denoise the EEG signals. Then the FastICA algorithm was used to separate the EEG signals from the EEG and ECG signals after denoising. Results The second-generation wavelet μ-law threshold method has a good de-noising effect on EEG signals. The FastICA algorithm can successfully separate the EEG and ECG interference in EEG. Conclusion It is an effective preconditioning method to separate the interference caused by independent sources by FastICA algorithm using the second generation wavelet μ law threshold method to denoise EEG.