摘要
为了剔除心电图(ECG)信号中的噪声,提出了一种基于改进小波阈值-CEEMDAN的去噪算法。首先对ECG信号进行CEEMDAN分解得到了一组由高频到低频分布的固有模态分量(IMF),然后根据相关系数法,对高频IMF分量进行改进阈值的小波去噪。对于低频IMF分量,再通过设定固定阈值,将低于该阈值的IMF分量确定为基线漂移信号并剔除,然后将去噪后的IMF分量和保留的IMF重构。实验结果表明,该算法相比经验模态分解(EMD)小波去噪和整体平均经验模态分解(EEMD)小波去噪算法效果更佳。
Electrocardiogram(ECG)signal denoising has always been a hot research issue.In order to eliminate the noises in ECG signal,a denoising method based on adaptive complete set empirical mode decomposition(CEEMDAN)and wavelet improved threshold function is proposed.Firstly,this method firstly decomposes the ECG signal by CEEMDAN to obtain a set of intrinsic modal functions(IMFs)from high frequency to low frequency.CEEMDAN decomposition is performed on ECG signal to yield several modal components(IMF).Secondly,the correlation coefficient method is used to perform wavelet denoising with improved threshold on the high frequency IMFs.For the low-frequency IMFs,by setting a fixed threshold,the IMFs below the threshold is considered to be the baseline drift signal and removed.Finally,the denoised IMFs and the retained IMFs are reconstructed.The experimental results show that the proposed method is more effective than the empirical mode decomposition(EMD)wavelet denoising,and the global average empirical mode decomposition(EEMD)wavelet denoising method.
作者
张培玲
李小真
崔帅华
ZHANG Pei-ling;LI Xiao-zhen;CUI Shuai-hua(School of Physics and Electronic Information Engineering,Henan Polytechnic University,Jiaozuo 454003;School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454003,China)
出处
《计算机工程与科学》
CSCD
北大核心
2020年第11期2067-2072,共6页
Computer Engineering & Science
基金
国家自然科学基金(41904078)
河南省教育厅科学技术研究重点项目(15A510008)。
