基于有限长脉冲响应滤波器和aTrous算法的小波心电信号去噪

微弱低频的心电信号采集中容易受到外界环境的干扰,必须先对其进行预处理才能用于心脏疾病的诊断。Mallat算法的小波分解重构法不能有效滤除心电信号中的工频和肌电干扰；小波阈值法不能有效滤除心电信号中的工频和基线漂移,重构的心电信号会产生伪吉布斯现象。针对以上情况,提出了一种基于有限长脉冲响应滤波器(FIR)和aTrous算法的小波去噪方法。该方法综合运用了50Hz陷波器、aTrous算法小波分解重构法和小波阈值法。仿真郑州大学第二附属医院和MIT-BIH心率失常数据库的心电信号表明,该方法能够有效去除心电信号中的工频和基线漂移,大幅度衰减肌电干扰,同时有效消除伪吉布斯现象。

Denosing of ECG signal based on FIR and aTrous wavelet transform

The weak and low-frequency Electrocardiogram(ECG) signals which can be used for disease diagnosis after preprocessing are susceptible to interference from the external environment.The wavelet decomposition and re-construction can not effectively filter out the 50 Hz frequency and EMG interference of which the frequency band is the same with the ECG,the wavelet thresholding method can not effectively filter out the baseline drift,and this method can cause Pseudo-Gibbs phenomenon in the signal singular points.In order to denoise effectively,a wavelet denoising method based on aTrous algorithm was proposed in this paper,and this method was a comprehension of the wavelet reconstruction and decomposition,wavelet thresholding and 50 Hz notch filter.The clinical ECG simulation results show that this method can effectively remove the ECG baseline drift,50 Hz frequency interference and EMG interference,while reducing the Gibbs phenomenon.