[1]王晓燕,鲁华祥,金敏,等.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.[doi:10.11992/tis.201611017]
 WANG Xiaoyan,LU Huaxiang,JIN Min,et al.Wavelet entropy denoising algorithm of electrocardiogram signals based on correlation[J].CAAI Transactions on Intelligent Systems,2016,11(6):827-834.[doi:10.11992/tis.201611017]
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基于相关性的小波熵心电信号去噪算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第11卷
期数:
2016年6期
页码:
827-834
栏目:
出版日期:
2017-01-20

文章信息/Info

Title:
Wavelet entropy denoising algorithm of electrocardiogram signals based on correlation
作者:
王晓燕1 鲁华祥12 金敏1 龚国良1 毛文宇1 陈刚1
1. 中国科学院 半导体研究所, 北京 100083;
2. 中国科学院 脑科学与智能技术卓越创新中心, 上海 200031
Author(s):
WANG Xiaoyan1 LU Huaxiang12 JIN Min1 GONG Guoliang1 MAO Wenyu1 CHEN Gang1
1. Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China;
2. Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
关键词:
心电信号去噪相关性小波熵自适应
Keywords:
electrocardiogram signalsdenoisingcorrelationwavelet entropyadaptively
分类号:
TP391
DOI:
10.11992/tis.201611017
摘要:
针对心电信号的基线漂移、工频噪声、肌电噪声,本文提出了基于相关性的小波熵去噪算法。算法首先根据基线漂移的低频特性,确定小波分解的层数,置零近似系数,去除基线漂移;再对相邻尺度的高频小波系数进行相关处理,依据小波熵自适应地计算全局阈值去除工频和肌电噪声;最后将置零的近似系数和阈值处理后的小波系数重构得到有效信号。该算法能够在一次小波分解、重构的过程中,同时滤除心电信号中的3种主要噪声。对MIT-BIH数据库数据和模拟数据的仿真实验结果也表明该算法的去噪效果显著优于其他算法。
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.

参考文献/References:

[1] 赵艳娜, 魏珑, 徐舫舟, 等. 基于小波变换的心电信号去噪综合算法[J]. 现代生物医学进展, 2009, 9(16):3128-3130. ZHAO Yanna, WEI Long, XU Fangzhou, et al. ECG signal denoising algorithm based on wavelet transform[J]. Progress in modern biomedicine, 2009, 9(16):3128-3130.
[2] HARITHA C, GANESAN M, SUMESH E P. A survey on modern trends in ECG noise removal techniques[C]//Proceedings of 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). Nagercoil:IEEE, 2016:1-7.
[3] 赵志华, 许爱华. 基于形态学的ECG小波自适应去噪算法[J]. 计算机工程与设计, 2008, 29(8):2140-2142. ZHAO Zhihua, XU Aihua. ECG adaptive wavelet transform of denoising algorithm based on morphology[J]. Computer engineering and design, 2008, 29(8):2140-2142.
[4] TAI Shenchuan, SUN C C, YAN W C. A 2-D ECG compression method based on wavelet transform and modified SPIHT[J]. IEEE transactions on biomedical engineering, 2005, 52(6):999-1008.
[5] 杨思军, 郝继飞, 闫文杰, 等. 小波滤波与QRS波检测[J]. 计算机工程与应用, 2011, 47(12):239-241. YANG Sijun, HAO Jifei, YAN Wenjie, et al. Wave filtering and QRS detection[J]. Computer engineering and applications, 2011, 47(12):239-241.
[6] DONOHO D L. denoising by soft-thresholding[J]. IEEE transactions on information theory, 1995, 41(3):613-627.
[7] AGANTE P M, DE SA J P M. ECG noise filtering using wavelets with soft-thresholding methods[C]//Proceedings of 1999 Computers in Cardiology. Hannover:IEEE, 1999, 26:523-538.
[8] 侯宏花, 桂志国. 基于小波熵的心电信号去噪处理[J]. 中国生物医学工程学报, 2010, 29(1):22-28, 34. HOU Honghua, GUI Zhiguo. Denosing processing of ECG signal based on wavelet entropy[J]. Chinese journal of biomedical engineering, 2010, 29(1):22-28, 34.
[9] 欧阳波, 程栋, 王玲. 改进小波阈值算法在心电信号去噪中的应用[J]. 计算机工程与应用, 2015, 51(4):213-217. OUYANG Bo, CHENG Dong, WANG Ling. Improved wavelet threshold algorithm in application of ECG signal de-noising[J]. Computer engineering and applications, 2015, 51(4):213-217.
[10] LI Nianqiang, LI Ping. An improved algorithm based on EMD-wavelet for ECG signal de-nosing[C]//Proceedings of 2009 International Joint Conference on Computational Sciences and Optimization. Sanya, China:IEEE, 2009, 1:825-827.
[11] MALLAT S. 信号处理的小波导引[M]. 北京:机械工业出版社, 2003.
[12] 刘霞, 黄阳, 黄敬, 等. 基于经验模态分解(EMD)的小波熵阈值地震信号去噪[J]. 吉林大学学报:地球科学, 2016, 46(1):262-269. LIU Xia, HUANG Yang, HUANG Jing, et al. Wavelet entropy threshold seismic signal denoising based on empirical mode decomposition (EMD)[J]. Journal of Jilin university:earth science edition, 2016, 46(1):262-269.
[13] 李文, 刘霞, 段玉波, 等. 基于小波熵与相关性相结合的小波模极大值地震信号去噪[J]. 地震学报, 2012, 34(6):841-850. LI Wen, LIU Xia, DUAN Yubo, et al. Wavelet modulus maxima denoising of seismic signals based on combined wavelet entropy and correlation[J]. Acta seismologica sinica, 2012, 34(6):841-850.
[14] ROSSO O A, BLANCO S, YORDANOVA J, et al. Wavelet entropy:a new tool for analysis of short duration brain electrical signals[J]. Journal of neuroscience methods, 2001, 105(1):65-75.
[15] 朱泽煌, 胡广书, 郭恒, 等. MIT-BIH心电数据库的开发及用作检测标准[J]. 中国生物医学工程学报, 1993, 12(4):244-249, 243.
[16] 徐效文, 曾超, 崔松野, 等. MIT-BIH数据库心电数据重采样研究[J]. 计算机工程与应用, 2011, 47(8):245-248. XU Xiaowen, ZENG Chao, CUI Songye, et al. Research on resampling of ECG data from MIT-BIH database[J]. Computer engineering and applications, 2011, 47(8):245-248.

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备注/Memo

备注/Memo:
收稿日期:2016-11-15。
基金项目:中国科学院战略性先导专项(xdb02080002);青年自然科学基金项目(61401423);中国科学院国防实验室基金项目(CXJJ-16S076).
作者简介:王晓燕,女,1992年,硕士研究生,主要研究方向为信号处理、机器学习;鲁华祥,男,1965年,研究员,博士生导师,中国人工智能学会"神经网络与计算智能"专业委员会主任、中科院半导体所高速电路与神经网络实验室主任,主要研究方向为类脑神经计算方法、微电子类神经计算芯片和系统研究、不确定性及非完全信息处理。获北京市科学技术进步一等奖、"中国科学院盈科优秀青年学者奖"、国家发明三等奖、"国家‘八五’科技攻关重大科技成果奖"、"95电子十大科技成果奖"、全军科技进步二等奖等奖励。发表学术论文30余篇,合作出版专著1本,获授权发明专利10项;金敏,女,1985年,助理研究员,主要研究方向为信号处理、智能计算。
通讯作者:鲁华祥.E-mail:luhx@semi.ac.cn.
更新日期/Last Update: 1900-01-01