陡脉冲干扰下的心电信号滤波及QRS提取

为消除陡脉冲带来的干扰，分析了陡脉冲干扰的特点，建立了陡脉冲噪声数学模型，提出了基于变分模态分解（Variational mode decomposition, VMD）的心电信号滤波算法，提取叠加在心电信号中陡脉冲干扰分量、识别陡脉冲干扰分量并剔除陡脉冲干扰分量；为减少VMD分解层数、提高实时性并减少内存消耗，提出了心电信号预处理算法；针对医疗环境中的随机噪声伴随陡脉冲出现的情况，分析了VMD后子信号中随机噪声的特点，提出了基于VMD子信号能量估计的阈值去噪算法；利用变分模态分解的带通滤波器组特性，提出了基于变分模态分解子信号重组的QRS波群检测算法，配合滤波算法以提高心电信号特征检测精度。以添加了高斯白噪声和模拟陡脉冲干扰的MIT?BIH数据库心电信号和医疗环境中采集的心电信号为实验对象，分别实现对滤波算法和QRS波群检测算法的定量对比分析。 

ECG filtering and QRS extraction under steep pulse interference

Applying a steep pulse voltage of appropriate amplitude to a cell membrane can induce transient and reversible breakdown of the membrane, which has broad application prospects in biomedicine and clinical fields. However, the noise generated by the steep pulse seriously interferes with a patient’s electrocardiogram (ECG) signal resulting in decrease in the accuracy of the ECG feature point detection algorithm. Thus, doctors are unable to understand the state of the patient during treatment, thus limiting complete benefits of the therapy. To eliminate the interference caused by the steep pulse, we analyzed the characteristics of steep pulse interference and established the mathematical model of steep pulse noise. Moreover, we proposed an ECG signal filtering algorithm based on variational mode decomposition (VMD) to extract the steep pulse interference component superimposed on the ECG signal. The proposed algorithm could identify and eliminate the steep pulse interference component. We also designed an ECG signal preprocessing algorithm to reduce the decomposition layer of the VMD algorithm, which improved the real-time performance and reduced the memory consumption. To identify the random noise in the medical environment accompanied by the occurrence of steep pulses, we analyzed the characteristics of random noise in the sub-signal after VMD. Further, we proposed a threshold denoising algorithm based on VMD for sub-signal energy estimation. On the basis of the characteristics of a band-pass filter bank with VMD, we proposed a QRS complex detection algorithm based on VMD sub-signal recombination. Combined with the filtering algorithm, the proposed algorithm was able to improve the accuracy of ECG signal detection. By conducting experiments on ECG signals from the MIT–BIH database with Gaussian white noise and simulated steep pulse interference and those collected in the medical environment, we compared and analyzed the filtering algorithm and QRS complex detection algorithm.