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针对心电图(ECG)信号去噪问题,提出了一种基于集合经验分解(EEMD)和改进阈值函数的小波变换去噪方法。首先利用EEMD对含噪的ECG信号进行分解,选取固有模态函数(IMF),重构ECG信号,实现ECG信号的一次去噪;再利用改进阈值函数的小波变换方法对ECG信号进一步去噪。实验中,利用MIT-BIH心电图数据库对提出的方法进行评估,用参数信噪比(SNR)和均方误差(MSE)比较EEMD、改进阈值函数的小波变换方法以及本文提出的方法的去噪效果。实验结果表明:本文提出的方法去噪后的ECG信号波形平滑,特征点幅值无衰减,在去噪的同时更好地保留了原始ECG信号的特征。
Aiming at the problem of ECG signal denoising, a wavelet denoising method based on ensemble empirical decomposition (EEMD) and improved threshold function is proposed. Firstly, EEMD is used to decompose the noisy ECG signal. The IMF is selected to reconstruct the ECG signal to achieve a one-time denoising of the ECG signal. The ECG signal is further denoised by a wavelet transform method with improved threshold function. In the experiment, the proposed method was evaluated using the MIT-BIH ECG database, the EEMD was compared with the parametric SNR and the mean square error (MSE), the wavelet transform to improve the threshold function and the denoising effect of the proposed method . The experimental results show that the proposed method has the advantages of smoothing of the waveform of the de-noised ECG signal and no attenuation of the amplitude of the feature points, and better preserves the characteristics of the original ECG signal while denoising.