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心电信号是典型的强噪声下的非平稳微弱信号,减小噪声的干扰对心电信号的分析有着十分重要的意义,因此,有效的滤波方法一直是该领域学者关注的热点问题。本文在基于小波变换心电信号分析研究基础上,针对小波去噪时分解只作用于低频部分,从而忽略了高频区域中一部分有用信号的问题,提出了一种采用改进小波包理论实现心电信号去噪的方法,利用小波包在消除信号噪声方面具有更为精确的局部分析能力的特点,采用了‘db4’小波和“最优基”选择的方法,对心电信号进行消噪。以MIT-BIH心电数据库中心律失常数据仿真实验,得到了较理想的去噪效果。对比该方法与小波滤波去噪,发现基于小波包的心电信号去噪具有更优良的去噪性能。
ECG signal is a typical non-stationary weak signal under strong noise. It is very important to reduce the interference of noise on the ECG signal analysis. Therefore, effective filtering methods have been the hot issues in this field. In this paper, based on wavelet transform ECG signal analysis and research, aiming at the wavelet denoising when the decomposition only affects the low frequency part, thus ignoring the part of the high frequency region of the useful signal problem, proposed an improved wavelet packet theory to achieve ECG Signal denoising method, using wavelet packet in the elimination of signal noise with more accurate local analysis of the characteristics of the use of ’db4’ wavelet and “optimal base ” selection method, the ECG signal denoising . With MIT-BIH ECG arrhythmia data simulation experiments, the ideal denoising effect was obtained. Compared with the wavelet denoising, this method has better denoising performance based on wavelet packet denoising.