165
Views
6
CrossRef citations to date
0
Altmetric
Innovations

A hybrid algorithm for heart sounds segmentation based on phonocardiogram

Pages 363-377 | Received 22 Nov 2018, Accepted 28 Sep 2019, Published online: 23 Oct 2019

References

  • Ismail S, Siddiqi I, Akram U. Localization and classification of the heart beat in phonocardiography signals—a comprehensive review. EURASIP J Adv Signal Process. 2018;2018:26.
  • Castells F, Laguna P, Ornmo LS, et al. The principal component analysis in ECG signal processing. EURASIP J Adv Signal Process. 2007;2007(1):98.
  • Minhthang Bui F, Hatzinakos D. Biometric methods for secure communications in body sensor networks: resource-efficient key management and signal-level data scrambling. EURASIP J Adv Signal Process. 2008;2008:529879.
  • Sepulveda-Cano LM, Gil E, Laguna P, et al. Selection of nonstationary dynamic features for obstructive sleep apnoea detection in children. EURASIP J Adv Signal Process. 2011;2011(1):538314.
  • Nemati S, Malhotra A, Clifford GD. Data fusion for improved respiration rate estimation. EURASIP J Adv Signal Process. 2010;2010:926305.
  • Karnath B, Thornton W. Auscultation of the heart. Rev Clin Signs. 2002;38:39–43.
  • Zhong J, Scalzo F. Automatic heart sound signal analysis with reused multi-scale wavelet transform. Int J Eng Sci. 2013;2(7):50–57.
  • Gill D, Gavrieli N, Intrator N. Detection and identification of heart sounds using homomorphic envelogram and self-organizing probabilistic model. Comput Cardiol. 2005;32:957–960.
  • Wang P, Kim Y, Ling LH, et al. First heart sound detection for phonocardiogram segmentation. Proceedings of the 2005 IEEE Engineering in Medicine and Biology, 27th Annual Conference; Shanghai, China; 2005. p. 5519–5523.
  • Gupta CN, Palaniappan R, Swaminathan S. Classification of homomorphic segmented phonocardiogram signals using grow and learn network. 27th Annual Conference of the IEEE Engineering in Medicine and Biology; Shanghai, China; 2005. p. 4251–4254.
  • Kumar D, Carvalho P, Antunes M, et al. Detection of S1 and S2 heart sounds by high-frequency signatures. Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society Conference. Vol. 1; 2006. p. 1410–1416.
  • Kumar D, Carvalho P, Antunes M, et al. Third heart sound detection using wavelet transform-simplicity filter. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:1277–1281.
  • Vladimir K, Polyshchuk V, Roy DL. Heart energy signature spectrogram for cardiovascular diagnosis. BioMed Eng OnLine. 2007;6:16.
  • Cherif LH. Segmentation of heart sounds and heart murmurs. J Mech Med Biol. 2008;8(4):549–559.
  • Quiceno AF, Delgado E, Vallverd M, et al. Effective phonocardiogram segmentation using nonlinear dynamic analysis and high-frequency decomposition. Comput Cardiol. 2008;35:161–164.
  • Bunluechokchai C, Ussawawongaraya W. A wavelet-based factor for classification of heart sound with mitral regurgitation. Int J Appl Biomed Eng. 2009;2(1):44–48.
  • Schmidt SE, Holst-Hansen C, Graff C, et al. Segmentation of heart sound recordings by a duration-dependent hidden Markov model. Physiol Meas. 2010;31:513–529.
  • Tseng YL, Ko PY, Jaw FS. Detection of the third and fourth heart sounds using the Hilbert–Huang transform. Biomed Eng OnLine. 2012;11(1):8–23.
  • Jinqun L, Wuchang L, Haibin W, et al. A novel envelope extraction method for multichannel heart sounds signal detection. Proceedings of 2011 International Conference on Computer Science and Information Technology (ICCSIT 2011) IPCSIT. Vol. 51; 2012. p. 630–638.
  • Fumio N, Yasunai Y, Yoko K, et al. Audio-visual based recognition of auscultator heart sounds with Fourier and wavelet analysis. Trans Biomed Eng Image Recogn. 2012;3:42–48.
  • Kouras N, Boutana D, Benidir M. Wavelet-based segmentation and time–frequency characterization of some abnormal heart sound signals. 24th International Conference on Microelectronics (ICM); 2012.
  • Boutana D, Barkat B, Benidir M. Segmentation of pathological heart sound signal using empirical mode decomposition. Int J Comput Electr Eng. 2013;5(1):26–29.
  • Mondal A, Bhattacharya P, Saha G. An automated tool for localization of heart sound components S1, S2, S3, and S4 in pulmonary sounds using Hilbert transform and Heron’s formula. SpringerPlus. 2013;2:14.
  • Atbi A, Debbal SM, Meziani F, et al. Separation of heart sounds and heart murmurs by Hilbert transform envelogram. J Med Eng Technol. 2013;37(6):375–387.
  • Pedrosa J, Castro A, Vinhoza TT. Automatic heart sound segmentation and murmur detection in pediatric phonocardiograms. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:2294–2297.
  • NivithaVarghees V, Ramachandran KI. A novel heart sound activity detection framework for automated heart sound analysis. Biomed Signal Process Control. 2014;13:174–188.
  • Elgendi M, Kumar S, Guo L, et al. Detection of heart sounds in children with and without pulmonary arterial hypertension―Daubechies wavelets approach. PLoS One. 2015;10(12):e0143146.
  • Randhawa SK, Singh M. Classification of heart sound signals using multi-modal features. Proc Comput Sci. 2015;58:165–171.
  • Chen T, Xiang L, Zhang M. Recognition of heart sound based on the distribution of Choi-Williams. Res Biomed Eng. 2015;31(3):189–195.
  • Golpaygani AT, Abolpour N, Hassani K, et al. Detection and identification of S1 and S2 heart sound using wavelet decomposition method. Int J Biomath. 2015;8(6).
  • NivithaVarghees V, Ramachandran KI. Multistage decision-based heart sound delineation method for automated analysis of heart sounds and murmurs. Health Technol Lett. 2015;2(6):156–163.
  • Hamidah A, Saputra R, Mengko TLR, et al. Effective heart sounds detection method based on the signal's characteristics. Conference Proceedings of the International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS); 2016.
  • Gavrovska A, Zajić G, Bogdanović V, et al. Identification of S1 and S2 heart sound patterns based on fractal theory and shape context. Complexity. 2017;2017:1.
  • Deperlioglu O, Mahallesi E, Gazlıgöl Y, et al. Segmentation of heart sounds by re-sampled signal energy method. Broad Res Artif Intell Neurosci. 2018;9(1):17–28.
  • [cited 2017 Mar 1]. Available from: www.physionet.org/challenge/2016/
  • Huang NE, Shen Z, Long SR, et al. The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. Proc R Soc Lond A. 1998;454(1971):903–995.
  • Wu Z, Huang NE. On the filtering properties of the empirical mode decomposition. Adv Adapt Data Anal. 2010;02(04):397–414.
  • Bulbul HI, Karaci A. Speech command recognition. Kastamonu Educ J. 2007;15(1):45–62.
  • Doga S. Recognition of voice commands in the PC environment [master thesis]. İstanbul: Marmara University, İnstitute of Science and Technology; 1999.
  • Addison PS. The Illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance. Bristol, UK: Institute of Physics Publications; 2002.
  • Nogata F, Yokota Y, Kawanura Y, et al. Audio-visual based recognition of auscultatory heart sounds with Fourier and wavelet analyses. Trans Biomed Eng Image Recogn. 2012;3:42–48.
  • Choi S, Jiang Z. Comparison of envelope extraction algorithms for cardiac sound signal segmentation. Expert Syst Appl. 2008;34(2):1056–1069.
  • Ari S, Saha G. On a robust algorithm for heart sound segmentation. J Mech Med Biol. 2007;7(2):129–150.
  • Samjin C, Zhongwei J. Comparison of envelope extraction algorithms for cardiac sound signal segmentation. Japan: Micro-Mechatronics Laboratory, Yamaguchi University; 2006.
  • Santos S, Carvalho P, Paiva RP, et al. Detection of the S2 split using the Hilbert and wavelet transforms. Congresso de Métodos Numéricos em Engenharia; 2011.
  • Zin ZM, Salleh SH, Daliman S, et al. Analysis of heart sounds based on continuous wavelet transform. IEEE Conference on Research and Development; 2003. p. 19–22.
  • Mgdob HM, Torry JN, Vincent R, et al. Application of Morlet transform wavelet in the detection of the paradoxical splitting of the second heart sound. IEEE Computers in Cardiology; 2003. p. 323–326.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.