Detection method of early heart valve diseases based on heart sound features_Journal of Biomedical Engineering

Authors：

SUN Chengfa , WANG Xinpei ,  LIU Changchun

School of Control Science and Engineering, Shandong University, Jinan 250061, P. R. China;

Corresponding author：

LIU Changchun, Email: changchunliu@sdu.edu.cn

Keywords：

Heart valve disease; Heart sound features; Envelope autocorrelation; Feature selection

DOI：

10.7507/1001-5515.202112009

Video：

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Abstract Full text Figures/Tables Video References Cited by

Heart valve disease (HVD) is one of the common cardiovascular diseases. Heart sound is an important physiological signal for diagnosing HVDs. This paper proposed a model based on combination of basic component features and envelope autocorrelation features to detect early HVDs. Initially, heart sound signals lasting 5 minutes were denoised by empirical mode decomposition (EMD) algorithm and segmented. Then the basic component features and envelope autocorrelation features of heart sound segments were extracted to construct heart sound feature set. Then the max-relevance and min-redundancy (MRMR) algorithm was utilized to select the optimal mixed feature subset. Finally, decision tree, support vector machine (SVM) and k-nearest neighbor (KNN) classifiers were trained to detect the early HVDs from the normal heart sounds and obtained the best accuracy of 99.9% in clinical database. Normal valve, abnormal semilunar valve and abnormal atrioventricular valve heart sounds were classified and the best accuracy was 99.8%. Moreover, normal valve, single-valve abnormal and multi-valve abnormal heart sounds were classified and the best accuracy was 98.2%. In public database, this method also obtained the good overall accuracy. The result demonstrated this proposed method had important value for the clinical diagnosis of early HVDs.

Citation： SUN Chengfa, WANG Xinpei, LIU Changchun. Detection method of early heart valve diseases based on heart sound features. Journal of Biomedical Engineering, 2023, 40(6): 1160-1167, 1174. doi: 10.7507/1001-5515.202112009 Copy

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21.	Li J H, Ke L, Du Q, et al. Heart sound signal classification algorithm: a combination of wavelet scattering transform and twin support vector machine. IEEE Access, 2019, 7: 179339-179348..
22.	Ding C, Peng H. Minimum redundancy feature selection from microarray gene expression data. J Bioinform Comput Biol, 2005, 3(2): 185-205..
23.	Ghosh S K, Ponnalagu R N, Tripathy R K, et al. Automated detection of heart valve diseases using chirplet transform and multiclass composite classifier with PCG signals. Comput Biol Med, 2020, 118: 103632..
24.	Claussen C D, Miller S, Fenchel M, et.al. 心脏影像学. 北京: 人民卫生出版社, 2015: 57-94..
25.	曹林生, 王朝晖, 王祥, 等. 心脏瓣膜病学. 北京: 科学技术文献出版社, 2002: 60-242..
26.	李治安, 杨娅. 超声心动图指南. 北京: 人民军医出版社, 2010: 70-112..
27.	Yaseen, Son G Y, Kwon S. Classification of heart sound signal using multiple features. Appl Sci, 2018, 8(12): 2344..
28.	Barua P D, Karasu M, Kobat M A, et al. An accurate valvular heart disorders detection model based on a new dual symmetric tree pattern using stethoscope sounds. Comput Biol Med, 2022, 146: 105599..
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1. Mozaffarian D, Benjamin E J, Go A S, et al. Executive summary: heart disease and stroke statistics——2016 update: a report from the American heart association. Circulation, 2016, 133(4): 447-454..
2. Savino K, Ambrosio G. Handheld ultrasound and focused cardiovascular echography: Use and information. Medicina, 2019, 55(8): 423..
3. Liang H, Lukkarinen S, Hartimo I. Heart sound segmentation algorithm based on heart sound envelogram. Comput Cardiol, 1997, 24: 105..
4. Boutana D, Benidir M, Barkat B. Segmentation and time-frequency analysis of pathological heart sound signals using the EMD method//22nd European Signal Processing Conference (EUSIPCO), Lisbon: IEEE, 2014: 1437-1441..
5. Schmidt S E, Holst-Hansen C, Graff C, et al. Segmentation of heart sound recordings by a duration dependent hidden Markov model. Physiol Meas, 2010, 31(4): 513-529..
6. Springer D B, Tarassenko L, Clifford G D. Logistic regression-HSMM-based heart sound segmentation. IEE Trans Biomed Eng, 2016, 63(4): 822-832..
7. Messner E, Zohrer M, Pernkopf F. Heart sound segmentation: an event detection approach using deep recurrent neural networks. IEEE Trans Biomed Eng, 2018, 65(9): 1964-1974..
8. Potes C, Parvaneh S, Rahman A, et al. Ensemble of feature-based and deep learning-based classifiers for detection of abnormal heart sounds// 2016 Computing in Cardiology Conference (CinC), Vancouver, Canada: IEEE, 2016: 621-624..
9. Chen J F, Dang X. Heart sound analysis based on extended features and related factors//2019 IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China: IEEE, 2019: 2189-2194..
10. Oztavli E, Aptoula E. Effect of early and late fusion on heart sound classification//2018 26th Signal Processing and Communications Applications Conference (SIU), Izmir: IEEE, 2018: 1-4..
11. Yadav A, Dutta M K, Travieso C M, et al. Automatic classification of normal and abnormal PCG recording heart sound recording using fourier transform//2018 IEEE International Work Conference on Bioinspired Intelligence, San Carlos, Costa Rica: IEEE, 2018: 1-9..
12. Upretee P, Yüksel M E. Accurate classification of heart sounds for disease diagnosis by a single time-varying spectral feature: preliminary results//2019 Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science, Istanbul, Turkey: IEEE, 2019: 1-4..
13. Krishnan P T, Balasubramanian P, Umapathy S. Automated heart sound classification system from unsegmented phonocardiogram (PCG) using deep neural network. Phys Eng Sci Med, 2020, 43(2): 505-515..
14. Meintjes A, Lowe A, Legget M. Fundamental heart sound classification using the continuous wavelet transform and convolutional neural networks//2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, USA: IEEE, 2018: 409-412..
15. Noman F, Ting C M, Salleh S H, et al. Short-segment heart sound classification using an ensemble of deep convolutional neural networks//2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK: IEEE, 2019: 1318-1322..
16. Singh S A, Majumder S, Mishra M. Classification of short unsegmented heart sound based on deep learning//2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Auckland, New Zealand: IEEE, 2019: 1-6..
17. Li J, Ke L, Du Q. Classification of heart sounds based on the wavelet fractal and twin support vector machine. Entropy, 2019, 21(5): 472..
18. Liu C, Springer D, Li Q, et al. An open access database for the evaluation of heart sound algorithms. Physiol Meas, 2016, 37(12): 2181-2213..
19. Fatemeh S, Asri R A R. RenyiBS: Renyi entropy basis selection from wavelet packet decomposition tree for phonocardiogram classification. J Supercomput, 2021, 77: 3710-3726..
20. Zheng Y N, Guo X M, Ding X R. A novel hybrid energy fraction and entropy-based approach for systolic heart murmurs identification. Expert Syst Appl, 2015, 42: 2710-2721..
21. Li J H, Ke L, Du Q, et al. Heart sound signal classification algorithm: a combination of wavelet scattering transform and twin support vector machine. IEEE Access, 2019, 7: 179339-179348..
22. Ding C, Peng H. Minimum redundancy feature selection from microarray gene expression data. J Bioinform Comput Biol, 2005, 3(2): 185-205..
23. Ghosh S K, Ponnalagu R N, Tripathy R K, et al. Automated detection of heart valve diseases using chirplet transform and multiclass composite classifier with PCG signals. Comput Biol Med, 2020, 118: 103632..
24. Claussen C D, Miller S, Fenchel M, et.al. 心脏影像学. 北京: 人民卫生出版社, 2015: 57-94..
25. 曹林生, 王朝晖, 王祥, 等. 心脏瓣膜病学. 北京: 科学技术文献出版社, 2002: 60-242..
26. 李治安, 杨娅. 超声心动图指南. 北京: 人民军医出版社, 2010: 70-112..
27. Yaseen, Son G Y, Kwon S. Classification of heart sound signal using multiple features. Appl Sci, 2018, 8(12): 2344..
28. Barua P D, Karasu M, Kobat M A, et al. An accurate valvular heart disorders detection model based on a new dual symmetric tree pattern using stethoscope sounds. Comput Biol Med, 2022, 146: 105599..
29. Bentley P J, Nordehn G, Coimbra M, et.al. The PASCAL classifying heart sounds challenge 2011. (2011-11-01) [2021-12-01]. http: //www.peterjbentley.com/heartchallenge/..

Journal of Biomedical Engineering

Detection method of early heart valve diseases based on heart sound features

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