基于形态学和提升小波的心电信号去噪方法研究
Research of Removing Noise In ECG Signal Based on Morphology and Lifting Wavelet
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摘要: 心电信号是一种典型的微弱信号,含有大量噪声,还具有强烈的非线性和非平稳性.针对传统小波计算量大,很难同时将心电信号中高频和低频噪声去除的问题,提出一种结合形态学与提升小波阈值去噪的算法,通过形态学滤波器去除信号的低频噪声,提升小波阈值去噪法去除信号中的高频噪声.经过对MIT-BIH心律失常数据库中的心电信号进行仿真,结果表明,结合形态学算法与提升小波去噪算法的去噪方法,能同时有效去除信号中的低频和高频噪声,提高了心电信号的质量.Abstract: ECG is a typical weak noise-corrupted signal, with strong non-linear and non-stationary feature. It is difficult for traditional wavelet de-noise algorithm to remove the high- and low- frequency noise concurrently and the computation expense is large. The method that combines morphology and lifting wavelet threshold de-noise is able to remove the low frequency noise by a morphological filter and suppress the high frequency noise by the lifting wavelet de-noise. Based on the data from MIT-BIH arrhythmia database, the simulation results show that the proposed method is capable to remove the high- and low-frequency noise of the ECG signal concurrently and improve the ECG signal quality.
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