基于集合经验分解与改进阈值函数的小波变换心电信号去噪方法研究

Research on ECG De-noising Method Based on Ensemble Empirical Mode Decomposition and Wavelet Transform Using Improved Threshold Function

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。

A de-noising method for electrocardiogram （ECG） based on ensemble empirical mode decomposition （EE- MD） and wavelet threshold de-noising theory is proposed in our school. We decomposed noised ECG signals with the proposed method using the EEMD and calculated a series of intrinsic mode functions （IMFs）. Then we selected IMFs and reconstructed them to realize the de-noising for ECG. The processed ECG signals were filtered again with wavelet transform using improved threshold function. In the experiments, MIT-BIH ECG database was used for e- valuating the performance of the proposed method, contrasting with de-noising method based on EEMD and wavelet transform with improved threshold function alone in parameters of signal to noise ratio （SNR） and mean square error （MSE）. The results showed that the ECG waveforms de-noised with the proposed method were smooth and the am- plitudes of ECG features did not attenuate. In conclusion, the method discussed in this paper can realize the ECG de- noising and meanwhile keep the characteristics of original ECG signal.