基于小波变换的心电信号噪声处理

以小波变换的多分辨率分析为基础，通过对体表心电信号(ECG)及其噪声的分析，对ECG信号中存在的基线漂移、工频干扰及肌电干扰等几种噪声，设计了不同的小波消噪算法；并利用MIT／BIH国际标准数据库中的ECG信号和程序模拟所产生的ECG信号，分别对算法进行了仿真与实验验证。结果表明，算法能有效地滤除ECG信号检测中串入的几类主要噪声，失真度很小，可满足临床分析与诊断对ECG波形的要求。

Denoising of ECG Signals Based on Wavelet Transform

We apply the multi-resolution analysis(MRA) of wavelet transform(WT), which was proposed by Mallat [5], to suppress the three main types of noises existing in electrocardiogram(ECG) signals: baseline wander,powerline interference and electromyographical interference. We apply Mallat algorithm [4] to suppress the baseline wander in ECG signals. We apply the soft-thresholding algorithm, proposed by Donoho et al on the basis of MRA of WT,to suppress powerline interference in ECG signals. We apply Mallat algorithm and then the algorithm proposed by Donoho et al to suppress the electromyographical interference in ECG signals,whose frequency range varies from 5Hz to 2kHz.We performed simulations,using both ECG signals from MIT/BIH database, and ECG signals generated via computer simulation. The results show that the algorithm can suppress the main noises existing in ECG signals efficiently with very little distortion,and can satisfy the requirements of clinical analysis and diagnosis on ECG waveforms.