基于小波变换的心电信号去噪综合算法

ECG Signal Denoising Algorithm Based on Wavelet Transform

目的:研究去除心电信号中的基线漂移、工频干扰和肌电干扰等噪声,提高心电信号的自动识别和诊断精度。方法:利用Coif4小波对心电信号进行8尺度分解,采用小波分解重构法去除基线漂移,然后利用改进的小波阈值算法去除工频干扰和肌电干扰。结果:利用Matlab仿真工具,选择MIT-BIH心率失常数据库中信号进行验证,能有效去除这三种噪声,并且很好的保持R波的信息。结论:本算法在不丢失心电信号有用信息的前提下,可以较好的去除三种常见的噪声,可以用于心电信号自动分析之前的预处理。

Objective： To remove three kinds of noise in ECG signal： baseline drift,powedine interference and electromyographi- cal interference. Methods： Decompose ECG signal into eight layers using Coif4 wavelet, remove baseline drift using wavelet construction algorithm, then, remove powerline interference and electromyographical interference using an improved threshold method. Results： We choose some signals from MIT-BIH Arrhythmia Database; the results show that our method can effectively remove the mentioned noise, at the same time maintain R wave information. Conclusion： This algorithm can effectively remove three kinds of noise in ECG, thus can be used in ECG automatic analysis system.