基于双树复小波变换和形态学的脉搏信号去噪

De-noising method of pulse signal based on double-tree complex wavelet transform and morphological filtering

常见的医学信号(如脉搏信号)包含大量的噪声,具有强烈的非线性和非平稳性。针对传统的小波变换去噪方法的缺陷,提出了一种基于双树复小波变换和形态学的去噪算法,具有结构简单、计算复杂度低等优点,有效地克服了离散小波变换的平移敏感性和频率混淆。实验表明,该算法可以有效地去除脉搏信号中工频干扰及肌电干扰等高频噪声,其信噪比及均方差等定量指标均明显优于传统的阈值去噪算法,能得到较干净的脉搏信号波形。

Common medical signals such as pulse signals, contain a variety of noises, have strong nonlinear and non-stationary. According to the previous wavelet transformation method, a pulse signals de-noising algorithm based on dual-tree complex wavelet transform（DTCWT） was proposed. With the advantage of simple construction, clear mathematical implications and low computational complexity, this method overcame the shift sensitive and the frequency aliasing in the discrete wavelet transform. The simulation results show that this algorithm can remove the power line interference and EMG interference, and the quantitative index of SNR and mean square error is superior to the traditional threshold de-noising algorithm. Therefore, the dual-tree complex wavelet transform de-noising algorithm will obtain clear medical wave signals.