Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 210900135-6.doi: 10.11896/jsjkx.210900135

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Heart Sound Segmentation Algorithm Based on TK Energy Operator and Envelope Fusion

ZHANG Xin1, SUN Jing1, YANG Hong-bo2, PAN Jia-hua2, GUO Tao2, WANG Wei-lian1   

  1. 1 School of Information Science and Engineering,Yunnan University,Kunming 650504,China
    2 Yunnan Fuwai Cardiovascular Disease Hospital,Kunming 650102,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:ZHANG Xin,born in 1997,postgra-duate.Her main research interests include heart sound signal processing and so on.
    YANG Hong-bo,born in 1985,deputy chief physician,Ph.D candidate.His main research interests include clinical diagnosis,treatment and research of cardiovascular diseases.
  • Supported by:
    National Natural Science Foundation of China(81960067),Major Science and Technology Projects of Yunnan Province in 2018(2018ZF017) and Basic Research Program of Yunnan Province(Kunming-Medical Joint Special Project)(2018FE001)(-105).

PDF (PC)

303

Abstract: In order to segment heart sounds by component more effectively,a kind of heart sound segmentation algorithm based on Teager-Kaise energy operator(TKEO) and multi-envelope feature fusion is proposed in experiment.Firstly,the PCG signal is denoised by using the multi-scale wavelet soft threshold.Then TKEO operation is carried out.Since TKEO is extremely sensitive to the instantaneous energy change,the envelope peak can be extracted effectively and the TKEO signal can be obtained.Secondly,the normalized Shannon energy envelope and Viola integral envelope are extracted from the TKEO signal.The Pearson correlation coefficient between each envelope and TKEO signal is calculated.And then the fusion envelope is carried out according to the correlation.Next,the interval search method is used to search the peak envelopes.The variance of the search results is compared.Finally,false peaks are eliminated according to the maximum duration of S1 and S2.The proposed algorithm is tested using PhysioNet2016 data set.Experimental results show that an average accuracy of 0.922 is achieved by using this method.It is proved that this algorithm can be used to segment the heart sound signals effectively.It provides a new method for feature extraction and analysis of heart sound signals collected in clinical environment.

Key words: Heart sound segmentation, Teager-Kaise energy operator, Envelope fusion, Interval search, Wavelet denoising

CLC Number: 

  • TN912
[1]BERKAYA S K,UYSAL A K,GUNAL E S,et al.A survey on ECG analysis[J].Biomedical Signal Processing & Control,2018,43:216-235.
[2]HASSANI K,BAJELANI K,NAVIDBAKHSH M,et al.Heart sound segmentation based on homomorphic filtering[J].Perfusion,2014,29(4):351-359.
[3]SPRINGER D B,TARASSENKO L,CLIFFORD G D.Logistic regression-HSMM-based heart sound segmentation[J].IEEE Transactions on Bio-Medical Engineering,2016,63(4):822-832.
[4]WANG X Y,LIU C Y,LI Y W.Temporal-Framing AdaptiveNetwork for Heart Sound Segmentation without Prior Know-ledge of State Duration[J].IEEE Transactions on Biomedical Engineering,2020:650-663
[5]THARINDU F,HOUMAN G,SIMON D.Heart Sound Seg-mentation Using Bidirectional LSTMs With Attention[J].Journal of Biomedical and Health Informatics,2020,24(6):1601-1609.
[6]ALONSO ARÉVALO MIGUEL A,ALEJANDRO C.Robustheart sound segmentation based on spectral change detection and genetic algorithms[J].Biomedical Signal Processing and Control,2021,63:102208.
[7]MOUKADEM A,DIETERLEN A.A robust heart sounds segmentation module based on S-transform[J].Biomedical Signal Processing and Control,2013,8(3):229-332.
[8]RIEKE A D,POVINELLI R J,JOHNSON M T.Automatic segmentation of heart sound signals using hidden Markov models[C]//Computer sin Cardiology.Lyon,France:IEEE,2005:953-956.
[9]LIU C Y,SPRINGER D,CLIFFORD G D.Performance of anopen-source heart sound segmentation algorithm on eight independent databases[J].Physiological Measurement,2017,38(3):1730-1745.
[10]ZHOU S,ZHU D,WU X M,et al.Heart sound envelope extraction algorithm and application based on wavelet transform[J].Chinese Journal of Tissue Engineering Research,2011,15(30):5615-5619.
[11]JAMAL N,IBRAHIM N,SHA’ABANI M.Automated Heart Sound Signal Segmentation and Identification using Abrupt Changes and Peak Finding Detection[J].Procedia Computer Science,2021,179:260-267.
[12]LI J,LI X Y.HHT-based heart sound segmentation and medical index extraction[J].Control Engineering of China,2015,22(1):22-35.
[13]ZENG J Y,HE P Y,PAN F.Research on heart sound segmentation algorithm based on adaptive threshold[J].Sichuan University(Natural Science Edition),2019,56(5):867-874.
[14]LIU C,SPRINGER D,LI Q,et al.An open access database for the evaluation of heart sound algorithms[J].Physiological Measurement,2016,37(12):2181-2213.
[15]WANG X,LIU C,LI Y,et al.Temporal-Framing Adaptive Network for Heart Sound Semengtation without Prior Knowledge of State Duration[J].Biomedical Engineering,2020,68(2):650-663.
[1] YANG Yong-li,LIU Jian,ZHU Guang-xi. Channel Estimation Based on Block-thresholding Wavelet Denoising for System [J]. Computer Science, 2011, 38(6): 74-76.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.