智能系统学报2016，Vol.11Issue(6)：827-834,8.DOI:10.11992/tis.201611017
基于相关性的小波熵心电信号去噪算法
Wavelet entropy denoising algorithm of electrocardiogram signals based on correlation
摘要
Abstract
In view of the baseline drift, power line interference and muscle noise of electrocardiogram (ECG) signals, the wavelet entropy denoising algorithm of ECG signals based on correlation was proposed.First, ECG signals were decomposed using wavelets to determine the number of scale of wavelet decomposition, and the lowest approximation coefficients were each set to zero, so as to remove the baseline drift.Then, the high-frequency wavelet coefficient of adjacent scales was processed by adaptively calculating the global threshold with the correlation coefficients between the adjacent scales, to remove the power line interference and the muscle noise.Last, the denoising signals were reconstructed using zero approximation coefficients and processed wavelet coefficients.Using this method, three kinds of noise were removed in one process of wavelet decomposition and reconstruction.Experiments using the MIT-BIH database and simulative data prove that the algorithm is much better than others in ECG denoising with low complexity.关键词
心电信号/去噪/相关性/小波熵/自适应Key words
electrocardiogram signals/denoising/correlation/wavelet entropy/adaptively分类
信息技术与安全科学引用本文复制引用
王晓燕,鲁华祥,金敏,龚国良,毛文宇,陈刚..基于相关性的小波熵心电信号去噪算法[J].智能系统学报,2016,11(6):827-834,8.基金项目
中国科学院战略性先导专项(xdb02080002) （xdb02080002）
青年自然科学基金项目(61401423) （61401423）
中国科学院国防实验室基金项目(CXJJ-16S076). （CXJJ-16S076）
