一种ECG信号肌电干扰去除方法的研究
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摘要
实测心电(ECG)信号通常被多种因素干扰,尤其是肌电干扰的去除存在较大困难。本文提出一种结合经验模态分解法(EMD)与主成分分析(PCA)的消噪算法来去除ECG信号的肌电干扰。解决了通常采用小波算法和EMD等方法会导致ECG信号产生振荡和丢失有用信息的难题。本研究利用PCA对含噪信号经EMD分解后的内蕴模态函数(IMF)进行去噪处理,通过对MIT-BIH心电数据进行仿真,以及定性分析了信噪比(SNR)和均方误差(MSE)。结果表明,ECG信号中的肌电干扰被有效去除,所提方法的消噪效果整体上优于小波去噪算法和EMD消噪算法,是一种有效的消噪方法。
The Electrocardiogram( ECG) recording is often deteriorated by several factors,especially the myoelectricity interference removal is more difficult.In this paper,removing the electromygram from ECG signal based on empirical mode decomposition( EMD) and principal component analysis( PCA) de-nosing method has been proposed.The problem of shocking of ECG signal、lose some useful information by wavelet algorithm and EMD respectively has been solved.The method removed noise of intrinsic mode functions( IMFs) using PCA,after the noisy signal is decomposed by EMD.At last,the proposed method is evaluated over MIT-BIH ECG database in terms of visual inspection and qualitatively by signal noise ratio( SNR) and mean square error( MSE).The results show that the myoelectricity interference are removed efficiently and the proposed method outperforms wavelet de-noising algorithm and EMD de-noising algorithm.So it is an effective de-noising method.
The Electrocardiogram( ECG) recording is often deteriorated by several factors,especially the myoelectricity interference removal is more difficult.In this paper,removing the electromygram from ECG signal based on empirical mode decomposition( EMD) and principal component analysis( PCA) de-nosing method has been proposed.The problem of shocking of ECG signal、lose some useful information by wavelet algorithm and EMD respectively has been solved.The method removed noise of intrinsic mode functions( IMFs) using PCA,after the noisy signal is decomposed by EMD.At last,the proposed method is evaluated over MIT-BIH ECG database in terms of visual inspection and qualitatively by signal noise ratio( SNR) and mean square error( MSE).The results show that the myoelectricity interference are removed efficiently and the proposed method outperforms wavelet de-noising algorithm and EMD de-noising algorithm.So it is an effective de-noising method.
引文
[1]ANAPAGAMINI S A,RAJAVEL R.Removal of artifacts in ECG using empirical mode decomposition[C]//2013 International Conference on.Melmaruvathur:IEEE,2013:288-292.
[2]WENG Binwei,MANUEL B-V,BARNER K E.ECG denoising based on the empirical mode decomposition[C]//Proceedings of the28thIEEE EMBS Annual International Conference New York City.USA:IEEE,Aug 30-Sept 3,2006.
[3]王英,曾光宇.基于小波的EMD去噪法应用于心电信号去噪[J].数值计算与计算机应用,2011,32(4):274-282.
[4]王林泓,杨浩.心电信号处理中滤波器设计的研究[J].北京生物医学工程,2002,21(3):218-221.
[5]王秀云,严碧歌,马磊,等.基于小波变换心电信号消噪方法研究[J].现代生物医学进展,2008,8(10):1987-1988,1986.
[6]邹清,汤井田,唐艳.Hilbert-Huang变换应用于心电信号消噪[J].中国医学物理学杂志,2007,24(4):309-312.
[7]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.
[8]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of royal Society,1998,A454(1971):903-995.
[9]WU Zhaohua,NORDEN E H.A study of the characteristics of white noise using the empirical mode decomposition method[J].Proceedings of the Royal Society of London,2004,460(2046):1597-1611.
[10]ZHANG Lei,RASTISLAV L,WU Xiaolin.PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras[J].IEEE Transaction on Image Processing,2009,18(4):797-812.
[11]曲从善,路延镇,谭营.一种改进型经验模态分解及其在信号消噪中的应用[J].自动化学报,2010,36(1):67-73.
[12]KOPSINIS Y,MCLAUGHLI S.Development of EMD-based denois-ing methods inspired by wavelet thresholding[J].IEEE Transactions on Signal Processing,2009,57(4):1351-1362.
[13]FLANDRIN P,RILING G,GONCALVES P.Empirical mode decomposition as a filter bank[J].IEEE Signal Processing Letters,2004,11(2):112-114.
[14]行鸿彦,侯进勇.基于经验模式分解与独立分量分析的心电信号消噪方法[J].中国组织工程研究与临床康复,2009,13(4):651-654.
[2]WENG Binwei,MANUEL B-V,BARNER K E.ECG denoising based on the empirical mode decomposition[C]//Proceedings of the28thIEEE EMBS Annual International Conference New York City.USA:IEEE,Aug 30-Sept 3,2006.
[3]王英,曾光宇.基于小波的EMD去噪法应用于心电信号去噪[J].数值计算与计算机应用,2011,32(4):274-282.
[4]王林泓,杨浩.心电信号处理中滤波器设计的研究[J].北京生物医学工程,2002,21(3):218-221.
[5]王秀云,严碧歌,马磊,等.基于小波变换心电信号消噪方法研究[J].现代生物医学进展,2008,8(10):1987-1988,1986.
[6]邹清,汤井田,唐艳.Hilbert-Huang变换应用于心电信号消噪[J].中国医学物理学杂志,2007,24(4):309-312.
[7]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.
[8]HUANG N E,SHEN Z,LONG S R,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of royal Society,1998,A454(1971):903-995.
[9]WU Zhaohua,NORDEN E H.A study of the characteristics of white noise using the empirical mode decomposition method[J].Proceedings of the Royal Society of London,2004,460(2046):1597-1611.
[10]ZHANG Lei,RASTISLAV L,WU Xiaolin.PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras[J].IEEE Transaction on Image Processing,2009,18(4):797-812.
[11]曲从善,路延镇,谭营.一种改进型经验模态分解及其在信号消噪中的应用[J].自动化学报,2010,36(1):67-73.
[12]KOPSINIS Y,MCLAUGHLI S.Development of EMD-based denois-ing methods inspired by wavelet thresholding[J].IEEE Transactions on Signal Processing,2009,57(4):1351-1362.
[13]FLANDRIN P,RILING G,GONCALVES P.Empirical mode decomposition as a filter bank[J].IEEE Signal Processing Letters,2004,11(2):112-114.
[14]行鸿彦,侯进勇.基于经验模式分解与独立分量分析的心电信号消噪方法[J].中国组织工程研究与临床康复,2009,13(4):651-654.
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