基于coif-5小波的心音自适应阈值降噪方法
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摘要
为改善小波阈值及阈值函数在心音信号降噪处理中性能,通过使用coif-5小波做5层小波分解,抑制分量极少的层次的系数,保留有用分量层次的系数,然后引入相关统计参量进行阈值自适应估计,并按提出的阈值函数对有用分量层次系数阈值化处理,最后通过处理后的系数重构出降噪信号;所提方法与硬阈值、软阈值、线性中间阈值函数降噪性能进行了对比,并采用了三类评价指标做出了有效评价。实验结果表明:提出方法降噪后的信噪比更高、均方根误差更小、听诊平均意见得分更高。可见,提出方法降噪性能更优。
In order to improve the performance of wavelet threshold and threshold function in noise reduction processing of heart sound signals,there use the coif-5 wavelet to do 5 layers decomposition,restrain the coefficient of a low level of component and retain the useful component level. Then,statistical parameters are introduced to estimate the threshold adaptively,and threshold of useful components is thresholding according to the threshold function. Finally,reconstructing the signal after the noise reduction. The proposed method is compared with hard threshold,soft threshold and linear intermediate threshold function,and use three evaluation indexes to evaluate.The experimental results show that the proposed method has a higher signal-to-noise ratio,a smaller root mean square error and a higher auscultation mean opinion score. Therefore,the proposed method has better performance.
In order to improve the performance of wavelet threshold and threshold function in noise reduction processing of heart sound signals,there use the coif-5 wavelet to do 5 layers decomposition,restrain the coefficient of a low level of component and retain the useful component level. Then,statistical parameters are introduced to estimate the threshold adaptively,and threshold of useful components is thresholding according to the threshold function. Finally,reconstructing the signal after the noise reduction. The proposed method is compared with hard threshold,soft threshold and linear intermediate threshold function,and use three evaluation indexes to evaluate.The experimental results show that the proposed method has a higher signal-to-noise ratio,a smaller root mean square error and a higher auscultation mean opinion score. Therefore,the proposed method has better performance.
引文
1 Jain P K,Tiwari A K.Heart monitoring systems-A review[J].Computers in Biology&Medicine,2014,54(C):1-13
2 Chourasia V S,Tiwari A K,Gangopadhyay R.A novel approach for phonocardiographic signals processing to make possible fetal heart rate evaluations[J].Digital Signal Processing,2014,30(1):165-183
3 Gradolewski D,Redlarski G.Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment[J].Computers in Biology&Medicine,2014,52(3):119-129
4 Manikandan S M,Soman K P.Robust heart sound activity detection in noisy environments[J].Electronics Letters,2010,46(16):1100-1102
5 Song D,Jia L,Lu Y,et al.Heart sounds monitor and analysis in noisy environments[C]//International Conference on Systems and Informatics.New York:IEEE,2012:1677-1681
6 Vaisman S,Salem S Y.Passive fetal monitoring by adaptive wavelet denoising method[J].Computers in Biology&Medicine,2012,42(2):171-179
7 Zümray D,Tamer.Heart sound classification using wavelet transform and incremental self-organizing map[J],Digital Signal Processing,2008,18(6):951-959
8 Cherif H F,Debbal S,Bereksi-Reguig F.Choice of the wavelet analyzing in the phonocardiogram signal analysis using the discrete and the packet wavelet transform[J].Expert Systems with Applications,2010,37(2):913-918
9赵继印,刘海英,马洪顺,等.基于coif5小波的多普勒胎心音信号提取算法的研究[J].中国生物医学工程学报,2006,25(5):538-541Zhao Jiyin,Liu Haiying,Ma Hongshun,et al.Research of the approach for the fetal heart sound signal's extracting based on coif5wavelet transform[J].Chinese Journal of Biomedical Engineering,2006,25(5):538-541
10陈天华.基于现代信号处理技术的心音与心电信号分析方法[M].北京:机械工业出版社,2011:103-106Chen Tianhua.Analysis method of heart sound and electrocardiogram based on modern signal processing technology[M].Beijing:Machinery Industry Press,2011:103-106
11 Naseri H,Homaeinezhad M R,Pourkhajeh H.Noise/spike detection in phonocardiogram signal as a cyclic random process with nonstationary period interval[J].Computers in Biology&Medicine,2013,43(9):1205-1213
12 Agrawal K,Jha A K,Sharma S,et al.Wavelet subband dependent thresholding for denoising of phonocardi-ographic signals[C]//Signal Processing:Algorithms,Architectures,Arran-gements,and Applications(SPA).Poznan:The Institute of Electrical and Electronics Engineers INC,2013:158-162
13寇俊克,魏连鑫.基于小波分析的改进阈值去噪方法[J].科学技术与工程,2011,11(27):6724-6726Kou Junke,Wei Lianxin.Improved threshold denoising functions based on wavelet analysis[J].Science Technology and Engineering,2011,11(27):6724-6726
14 Singh J,Anand R S.Computer aided analysis of phonocardiogram[J].Journal of Medical Engineering&Technology,2007,31(5):319-323
15 Naseri H,Homaeinezhad M R.Detection and boundary identification of phonocardiogram sounds using an expert frequency-energy based metric[J].Annals of Biomedical Engineering,2013,41(2):279-292
16刘珊,李艳萍,胡欣宇.基于小波变换的新阈值法心电信号去噪的研究[J].科学技术与工程,2014,14(4):236-240+264Liu Shan,Li Yanping,Hu Xinyu.A novel thresholding method for removing electrocardiograph noises based on wavelet transform[J].Science Technology and Engineering,2014,14(4):236-240+264
17 Schwartz M.EMG methods for evaluating muscle and nerve function[M].Rijeka:InTech,2012:107-132
18 Jain P K,Tiwari A K.An adaptive thresholding method for the wavelet based denoising of phonocardiogram signal[J].Biomedical Signal Processing&Control,2017,38:388-399
19 Hu Y,Loizou P C.Subjective comparison and evaluation of speech enhancement algorithms[J].Speech Communication,2006,49(7):588-601
20 Saurabh Gupta M D,Andrew D,et al.Relationship between accurate auscultation of the fourth heart sound and the level of physician experience[J].Clinical Cardiology,2010,32(2):69-75
2 Chourasia V S,Tiwari A K,Gangopadhyay R.A novel approach for phonocardiographic signals processing to make possible fetal heart rate evaluations[J].Digital Signal Processing,2014,30(1):165-183
3 Gradolewski D,Redlarski G.Wavelet-based denoising method for real phonocardiography signal recorded by mobile devices in noisy environment[J].Computers in Biology&Medicine,2014,52(3):119-129
4 Manikandan S M,Soman K P.Robust heart sound activity detection in noisy environments[J].Electronics Letters,2010,46(16):1100-1102
5 Song D,Jia L,Lu Y,et al.Heart sounds monitor and analysis in noisy environments[C]//International Conference on Systems and Informatics.New York:IEEE,2012:1677-1681
6 Vaisman S,Salem S Y.Passive fetal monitoring by adaptive wavelet denoising method[J].Computers in Biology&Medicine,2012,42(2):171-179
7 Zümray D,Tamer.Heart sound classification using wavelet transform and incremental self-organizing map[J],Digital Signal Processing,2008,18(6):951-959
8 Cherif H F,Debbal S,Bereksi-Reguig F.Choice of the wavelet analyzing in the phonocardiogram signal analysis using the discrete and the packet wavelet transform[J].Expert Systems with Applications,2010,37(2):913-918
9赵继印,刘海英,马洪顺,等.基于coif5小波的多普勒胎心音信号提取算法的研究[J].中国生物医学工程学报,2006,25(5):538-541Zhao Jiyin,Liu Haiying,Ma Hongshun,et al.Research of the approach for the fetal heart sound signal's extracting based on coif5wavelet transform[J].Chinese Journal of Biomedical Engineering,2006,25(5):538-541
10陈天华.基于现代信号处理技术的心音与心电信号分析方法[M].北京:机械工业出版社,2011:103-106Chen Tianhua.Analysis method of heart sound and electrocardiogram based on modern signal processing technology[M].Beijing:Machinery Industry Press,2011:103-106
11 Naseri H,Homaeinezhad M R,Pourkhajeh H.Noise/spike detection in phonocardiogram signal as a cyclic random process with nonstationary period interval[J].Computers in Biology&Medicine,2013,43(9):1205-1213
12 Agrawal K,Jha A K,Sharma S,et al.Wavelet subband dependent thresholding for denoising of phonocardi-ographic signals[C]//Signal Processing:Algorithms,Architectures,Arran-gements,and Applications(SPA).Poznan:The Institute of Electrical and Electronics Engineers INC,2013:158-162
13寇俊克,魏连鑫.基于小波分析的改进阈值去噪方法[J].科学技术与工程,2011,11(27):6724-6726Kou Junke,Wei Lianxin.Improved threshold denoising functions based on wavelet analysis[J].Science Technology and Engineering,2011,11(27):6724-6726
14 Singh J,Anand R S.Computer aided analysis of phonocardiogram[J].Journal of Medical Engineering&Technology,2007,31(5):319-323
15 Naseri H,Homaeinezhad M R.Detection and boundary identification of phonocardiogram sounds using an expert frequency-energy based metric[J].Annals of Biomedical Engineering,2013,41(2):279-292
16刘珊,李艳萍,胡欣宇.基于小波变换的新阈值法心电信号去噪的研究[J].科学技术与工程,2014,14(4):236-240+264Liu Shan,Li Yanping,Hu Xinyu.A novel thresholding method for removing electrocardiograph noises based on wavelet transform[J].Science Technology and Engineering,2014,14(4):236-240+264
17 Schwartz M.EMG methods for evaluating muscle and nerve function[M].Rijeka:InTech,2012:107-132
18 Jain P K,Tiwari A K.An adaptive thresholding method for the wavelet based denoising of phonocardiogram signal[J].Biomedical Signal Processing&Control,2017,38:388-399
19 Hu Y,Loizou P C.Subjective comparison and evaluation of speech enhancement algorithms[J].Speech Communication,2006,49(7):588-601
20 Saurabh Gupta M D,Andrew D,et al.Relationship between accurate auscultation of the fourth heart sound and the level of physician experience[J].Clinical Cardiology,2010,32(2):69-75