Skip to main content
SpringerLink
Log in

Utilizing wavelet transform and support vector machine for detection of the paradoxical splitting in the second heart sound

  • Special Issue - Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Paradoxical splitting occurs when pulmonic valve (P2) closes before the aortic valve (A2). This causes second heart sound (S2) to be a single sound during inspiration and split during exhalation. Etiology delay in aortic closure: aortic stenosis, volume overload of left ventricle (LV), conduction defects in LV, and left bundle branch block (LBBB). In this article, a method was proposed in early detection of a reverse in the appearance of A2 and P2 within S2. This method is based on the time–frequency maps obtained with the continuous wavelet transform (CWT), namely, the Meyer wavelet. A number of patients with LBBB and others with fitted pacemakers were studied. The above method is combined with the support vector machine (SVM) and performance of this method is evaluated using classification accuracy (Ca), sensitivity (Se), specificity, positive, and negative predicted values. Results show that it is relatively easy to detect the reverse in A2 and P2 and the Ca and Se is 90.97 and 94.44%, respectively, for the sample of 42 patients whose data were collected from the Cardiology Department at Brighton and Sussex University Hospital in England.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Al-Naami B, Chebil J, Trabsheh B, Mgdob H (2006) Developing custom signal processing algorithm with lab view FPGA and compact RIO to detect the aortic stenosis disease. Proc―Int Conf―IEEE Comput Cardiol 33:193–196

    Google Scholar 

  2. Al-Naami B (2006) Identification of the paradoxical splitting of the second heart sound using the continuous wavelet transform. Res J Appl Sci 1(1):106–109

    Google Scholar 

  3. Balster D, Chan D (1997) Digital acoustic analysis of precordial innocent versus ventricular septal defect murmurs in children. Am J Cardiol 79:1552–1555

    Article  Google Scholar 

  4. Bentley PM, McDonnell JTE (1994) Wavelet transforms: an introduction. Electron Commun Eng J 6(4):175–186. doi:10.1049/ecej:19940401

    Article  Google Scholar 

  5. Bentley PM, McDonnell JTE (1994) Analysis of heart sounds using the wavelet transform. Proc―16th Int Conf―IEEE/EMBS 2:1304–1305

    Google Scholar 

  6. Bentley PM, McDonnell JTE, Grant PM (1998) Time-frequency and time-scale techniques for the classification of native and bioprosthetic heart valve sounds. IEEE Trans Biomed Eng 45(1):125–128

    Article  Google Scholar 

  7. Comak E, Polat K, Gunes S, Arslan A (2007) A new medical decision making system: least square support vector machine (LSSVM) with fuzzy weighting pre-processing. Expert Syst Appl 32(2):409–414

    Article  Google Scholar 

  8. Cortes C, Vapnik V (1995) Support vector networks. Mach Learn 20(3):273–297

    MATH  Google Scholar 

  9. Coubes JM, Grossmann A, Tchanmitchian Ph (1989) Wavelet time–frequency methods and phase space. Springer, IPTI, Berlin

    Google Scholar 

  10. Feigenil LP (1971) Physical characteristics of sound and hearing. Am J Cardiol 28(2):130–133

    Article  Google Scholar 

  11. Goupillan P, Grossmann A, Morlet J (1984/1985) Cycle-octave and related transform in seismics signal analysis. Geoexploration 23:85–102

    Google Scholar 

  12. Gupta CN, Palaniappan R, Swaminathan S, Krishnan SM (2007) Neural network classification of hormomorphic segmented heart sounds. Appl Soft Comput 7(1):286–297

    Article  Google Scholar 

  13. Huang CL, Wang CJ (2006) A GA-based feature selection and parameters optimization for support vector machines. Expert Syst Appl 31(2):231–240

    Article  Google Scholar 

  14. Hugonnet C, Walder P (1998) Stereophonic sound recording: theory and practice. Wiley, USA

    Google Scholar 

  15. Khadra L, El-Asir B, Mawagdeh S (1991) The wavelet transform and its applications to phonocardiogram signal analysis. Med Inform 16:271–277

    Article  Google Scholar 

  16. Kohavi R, Provost F (1998) Glossary of terms. Editorial for the special issue on Appl Mach Learn knowl Discov Proc 30(2–3)

  17. Leatham A (1987) Auscultation and phonocardiography: personal view of the past 40 years. Heart J 57(B2)

  18. Liang H, Lukkarinen S, Haritmo I (1997) A heart sound segmentation algorithm using wavelet decomposition and reconstruction. Proceedings―19th international conference―IEEE/EMBS, Chicago, IL, USA, vol 4, pp 1630–1633

  19. Luisada AA (1971) The second heart sound in normal and abnormal conditions. Am J cardiol 28(2):150–161

    Article  Google Scholar 

  20. Meyer, Y. (1990) Ondelettes et Opérateurs. Tome1, Herrmann, Paris

  21. Obaidat MS (1993) Phonocardiogram signal analysis: techniques and performance comparison. J Med Eng Technol 17:221–227

    Article  Google Scholar 

  22. Polat K, Gunes S, Arslan A (2008) A cascade learning system for classification of diabetes disease: generalized discriminant analysis and least square support vector machine. Expert Syst Appl 34(1):482–487

    Article  Google Scholar 

  23. Rangayyan RM, Lehner RJ (1988) Phonocardiogram signal processing: a review. CRC Crit Rev Biomed Eng 15(3):211–236

    Google Scholar 

  24. Samjin C (2008) Detection of valvular heart disorders using wavelet packet decomposition and support vector machine. Expert Syst Appl 35(4):1679–1687

    Article  Google Scholar 

  25. Swanton RH (1994) Cardiology, 3rd edn. Blackwell, Boston, USA, p 500

    Google Scholar 

  26. Taner T, Hüseyin P, İnan G (2008) Software development for the analysis of heart beat sounds with LabVIEW in diagnosis of cardiovascular disease. J Med Syst 32:409–421

    Article  Google Scholar 

  27. Tilkian G, Conover MB (2001) Understanding heart sounds and murmurs with the introduction to lung sounds, 4 editions. Saunders, USA, pp 9–72

  28. Tovar-Corona B, Torry JN (1998) Time-frequency representation of systolic murmurs using wavelets. Proceedings―international conference―IEEE computers in cardiology, Cleveland, USA, vol 25, pp 601–604

  29. Vapnik V (1995) The nature of statistical learning theory. Springer, New York

    MATH  Google Scholar 

  30. Wu CH, Tzeng GH, Goo YJ, Fang WC (2007) A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy. Expert Syst Appl 32(2):397–408. doi:10.1016/j.eswa.2005.12.008

    Article  Google Scholar 

  31. Zhong W, He J, Harrison R, Tai PC, Pan Y (2007) Clustering support vector machines for protein local structure prediction. Expert Syst Appl 32(2):518–526

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Hashemite University, P.O. Box 150459, Zarqa, 13115, Jordan

    Bassam Al-Naami, Jamal Al-Nabulsi & Hani Amasha

  2. Department of Engineering and Design, School of Science and Technology, University of Sussex, Brighton, Falmer, BN1 9QT, UK

    John Torry

Authors
  1. Bassam Al-Naami
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jamal Al-Nabulsi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hani Amasha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. John Torry
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bassam Al-Naami.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Al-Naami, B., Al-Nabulsi, J., Amasha, H. et al. Utilizing wavelet transform and support vector machine for detection of the paradoxical splitting in the second heart sound. Med Biol Eng Comput 48, 177–184 (2010). https://doi.org/10.1007/s11517-009-0548-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-009-0548-7

Keywords

Search

Navigation