• A. G. Rudnitskii Institute of hydromechanics NASU, Kyiv, Ukraine
  • M. A. Rudnytska Institute of hydromechanics NASU, Kyiv, Ukraine
  • L. V. Tkachenko Institute of hydromechanics NASU, Kyiv, Ukraine
Keywords: digital auscultation, noise suppression, Bayesian theorem, mathematical morphology


The paper considers a new method of separating respiratory sounds from heart sounds in a general signal registered on the surface of the human body. The proposed approach is based on a combination of Bayesian noise suppression techniques and methods of mathematical morphology. The proposed method was tested on real auscultatory signals. Evaluation of the efficiency of the algorithm using auditory, visual and numerical analysis shows that the developed approach is a promising alternative to existing techniques for separating auscultatory signals into its natural components.


Rudnitskii A.G. Mathematical morphology approach for single-channel processing of auscultative sound. Journal o f Applied Mathematics and Computation. 2019. 3(5), pp. 616–626.

Rudnitskii A.G. Two-Channel Processing of Signals for the Separation of Breath and Cardiac Sounds. Acoustical Physics. 2001. 47, N. 3, pp. 353–360.

Rudnitskii A.G. Using Nonlocal Means to Separate Cardiac and Respiration Sounds. Acoustical Physics. 2014. Vol. 60. No. 6, pp. 719–726.

Matheron G. Random sets and integral geometry. John Wiley & Sons, New York, 1975.

Van Trees H.L. Detection, Estimation and Modulation Theory: Part I. Wiley, 1968.

Ephraim Y., Malah D. Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator. IEEE Trans. Acoust., Speech, Signal Process. 1984. Vol. 32, pp. 1109–1121.

Heijmans H.J.A.M. Morphological image operators. Advances in electronics and electron physics, supplement. Academic Press, Boston, MA, 1994.

Makarenkov A.P., Rudnitskii A. G. Diagnosis of lung pathologies by two-channel processing of breathing sounds. Acoust. Phys. 1995. 41, pp. 234–238.