Skip to main content
SpringerLink
Log in

Spectral analysis of closing sounds produced by lonescu-Shiley bioprosthetic aortic heart valves

Part 1 Optimal number of poles and zeros for parametric spectral analysis

  • Computing and Data Processing
  • Published:
Medical and Biological Engineering and Computing Aims and scope Submit manuscript

Abstract

The selection of the optimal number of poles (P) and zeros (Q) for parametric spectral analysis of closing sounds produced by lonescu-Shiley bioprosthetic aortic heart valves was evaluated in 15 patients. These values were obtained by computing the normalised root-mean-square error (NRMSE) function between the aortic closing sounds and the impulse response of the parametric models for different values of P and Q. As expected, the NRMSE function decreased with increasing value of P and Q. The optimal P and Q were selected at the beginning of the plateau of the NRMSE function. For all-pole modelling with autocorrelation and all-pole modelling with covariance, the optimal number of poles is 16. For pole-zero modelling using the Steiglitz-McBride method with maximum entropy and extrapolation to zero, the optimum values are 14 poles and 14 zeros.

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

Similar content being viewed by others

Abbreviations

a k :

parameters describing the poles of the parametric model

APA:

all-pole modelling with autocorrelation method

APC:

all-pole modelling with covariance method

A 2 :

aortic component of the second heart sound

b r :

parameters describing the zeros of the parametric model

E :

square error

ms:

millisecond

NRMSE:

normalised root-mean-square error

P :

number of poles

Q :

number of zeros

SD:

standard deviation

SMME:

Steiglitz-McBride method with maximum entropy (pole-zero modelling)

SMEZ:

Steiglitz-McBride method with extrapolation to zero (pole-zero modelling)

S/N:

signal-to-noise

References

  • Akaike, H. (1970) Statistical predictor identification.Ann. Inst. Stat. Math.,22, 203–217.

    MATH  MathSciNet  Google Scholar 

  • Akaike, H. (1974) A new look at the statistical model identification.IEEE Trans.,AC-19, 716–723.

    MATH  MathSciNet  Google Scholar 

  • Childers, D. G. (1979) Modern spectral analysis. Proc. Frontiers Eng. in Health Care, IEEE, Colorado, 104–109.

  • Durand, L. G., de Guise, J., Cloutier, G., Guardo, R. andBrais, M. (1986) Evaluation of FFT-based and modern parametric methods for the spectral analysis of bioprosthetic valve sounds.IEEE Trans.,BME-33 572–578.

    Google Scholar 

  • Foale, R. A., Joo, T. H., McClellan, J. H., Metzinger, R. W., Grant, G. L., Myers, G. S. andLees, R. S. (1983) Detection of aortic porcine valve dysfunction by maximum entropy spectral analysis.Circulation,68, 42–49.

    Google Scholar 

  • Fougere, P. F., Zawalick, E. J., Radoski, H. R. (1976) Spontaneous line splitting in maximum entropy power spectrum analysis.Phys. Earth Planet. Int.,12, 201–207.

    Article  Google Scholar 

  • Gallucci, V., Valfré, C., Mazzucco, A., Bortolotti, U., Milans, A., Chioin, R., Dalla Volta, S. andCevese, P. G. (1982) Heart-valve replacement with the Hancock bioprosthesis: a 5–11 year follow-up. Cardiac Bioprostheses: Proceedings of the Second International Symposium.Cohn, L. H. andGallucci, V. (Eds.), Yorke Medical Books, New York, 9–24.

    Google Scholar 

  • Ionescu, M. I., Tandon, A. P., Saunders, N. R., Chidambarom, M. andSmith, D. R. (1982) Clinical durability of the pericardial xenograft valve: 11 years experience. Cardiac Bioprostheses: Proceedings of the Second International Symposium.Cohn, L. H. andGallucci, V. (Eds.), Yorke Medical Books, New York, 42–60.

    Google Scholar 

  • Joo, T. H. (1982) Pole-zero modeling and classification of phonocardiograms. Master's Thesis, Massachusetts Institute of Technology.

  • Joo, T. H., McClellan, J. H., Foale, R. A., Myers, G. S. andLees, R. S. (1983) Pole-zero modeling and classification of phonocardiograms.IEEE Trans.,BME-30, 110–118.

    Google Scholar 

  • Kay, S. andMarple, L. (1979) Sources of and remedies for spectral line splitting in autoregressive spectrum analysis. Conf. Rec.,IEEE Int. Conf. Acoust., Speech, Signal Processing, 151–154.

  • Lang, S. W. andMcClellan J. H. (1980) Frequency estimation with maximum entropy spectral estimators.IEEE Trans.,ASSP-28, 716–724.

    MATH  Google Scholar 

  • Makhoul, J. (1975) Linear prediction: a tutorial review.Proc. IEEE,63, 561–580.

    Article  Google Scholar 

  • Rabiner, L. R. andSchafer, R. W. (1978)Digital processing of speech signals. Prentice-Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

  • Steiglitz, K. andMcBride, L. E. (1965) Technique for the identification of linear systems.IEEE Trans.,AC-10, 161–164.

    Google Scholar 

  • Steiglitz, K. (1977) On the simultaneous estimation of poles and zeroes in speech analysis. ——Ibid.,ASSP-25, 229–234.

    Google Scholar 

  • Stein, P. D., Sabbah, H. N., Lakier, J. B. andGoldstein, S. (1980) Frequency spectrum of the aortic component of the second heart sound in patients with normal valves, aortic stenosis and aortic porcine xenografts.Am. J. Cardiol.,46, 48–52.

    Article  Google Scholar 

  • Stein, P. D., Sabbah, H. N., Lakier, J. B., Magilligan, D. J., andGoldstein, S. (1981) Frequency of the first heart sound in the assessment of stiffening of mitral bioprosthetic valves.Circulation,63, 200–204.

    Google Scholar 

  • Stein, P. D., Sabbah, H. N., Lakier, J. B., Kemp, S. R. andMagilligan, D. J. Jr. (1984) Frequency spectra of the first heart sound and of the aortic component of the second heart sound in patients with degenerated porcine bioprosthetic valves.Am. J. Cardiol.,53, 557–561.

    Article  Google Scholar 

  • Stoica, P. andSoderstrom, T. (1981) The Steiglitz-McBride identification algorithm revisited — convergence analysis and accuracy aspects.IEEE Trans.,AC-26, 712–717.

    MATH  MathSciNet  Google Scholar 

  • Thiene, G., Arbustini, E., Bortolotti, U., Talenti, E., Milano, A., Valente, M., Molin, G. andGallucci, V. (1982) Pathologic substrates of porcine valve dysfunction. Cardiac Bioprostheses: Proceedings of the Second International Symposium.Cohn, L. H. andGallucci, V. (Eds.), Yorke Medical Books, New York, 378–400.

    Google Scholar 

  • Vijaya Kumar, B. V. K. andMullick, S. K. (1979) Power spectrum estimation using maximum entropy method.J. Inst. Electron. & Telecomm. Eng.,25, 181–194.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Clinical Research Institute of Montreal, University of Montreal, and Biomedical Engineering Institute, École Polytechnique, University of Montreal, 110 Pine Avenue West, H2W 1R7, Montreal, Quebec, Canada

    G. Cloutier & L. -G. Durand

  2. Biomedical Engineering Institute, École Polytechnique, University of Montreal, Quebec, Canada

    R. Guardo

Authors
  1. G. Cloutier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. Guardo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. L. -G. Durand
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cloutier, G., Guardo, R. & Durand, L.G. Spectral analysis of closing sounds produced by lonescu-Shiley bioprosthetic aortic heart valves. Med. Biol. Eng. Comput. 25, 487–491 (1987). https://doi.org/10.1007/BF02441739

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02441739

Keywords

Search

Navigation