System of heart and lung sounds separation for store-and-forward telemedicine applications


  • Antonio José Salazar Universidad de los Andes
  • Catalina Alvarado Universidad de los Andes
  • Fernando Enrique Lozano Universidad de los Andes


Auscultation, cardiac sounds, pulmonary sounds, modulation filters, wavelet filters


Auscultation is a medical procedure that provides a general idea of heart and lung behavior as the physician listens to the breath sound. Due to the fact that the sounds from these organs overlap in time and frequency domains, important affections in one of them could be discarded. For instance, the objective of this work is to implement two different methods of cardiac and pulmonary sound separation. First, we apply modulation filters to the timefrequency representation of the original signal, recorded on the chest. Second, we apply an iterative algorithm of wavelet decomposition and reconstruction filters. Results show that they both separate signals appropriately. Taking lung signals as noise, we determine that signal to noise (SNR) ratio is 10.21 for the first method and for 6.61 the second. Applications in telemedicine are encourager since the bandwidth of the signal transmission could be reduced by sending it separately.

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L. Bickley, P. Szilagyi, B. Bates. Batesí guide to physical e amination and history taking. 8 ed. Ed. Lippincott Williams & Wilkins. Philadelphia, USA. 2003. pp 233-243, 277-295.

Z. Kazem, M. Zahra.. Fundamentals of respiratory sounds and analysis. Ed. Morgan & Claypool Publishers, series Synthesis lectures on biomedical engineering #8. San Rafael, CA, USA. 2006. pp. 19- 21.

V. Iyer, P. Ramamoorthy, F. Hong, Y. Plolysonsang. “Reduction of heart sounds from lung sounds by adaptive Filtering”. IEEE Trans. Biomed. Eng. Vol. 33. 1986. pp. 1141-1148.

S. Charleston, M. Azimi-Sadjadi. “Reduced order Kalman filtering for the enhancement of respiratory sounds”. IEEE Trans. Biomed. Eng. Vol. 43. 1996. pp. 421-424.

L. Hadjileontiadis, S. Panas. “Adaptive reduction of heart sounds from lung sounds using fourth-order statistics”. IEEE Trans. Biomed. Eng. Vol. 44. 1997. pp. 642-648.

L. Hadjileontiadis, S. Panas. “A wavelet-based reduction of heart sound noise from lung sounds”. Int. J. Med. Inf. Vol. 52. 1998. pp. 183-190.

M. Pourazad, Z. Moussavi, G. Thomas. “Heart sound cancellation from lung sound recordings using timefrequency filteringî. Med. Biol. Eng. Comput. Vol. 44. 2006. pp. 216-225.

I. Hossain, Z. Moussavi. An overview of heart-noise reduction of lung sound using wavelet transform based filter. in Proc. Ann. Int. Conf. IEEE EMBS. Cancún, México. 2003. pp. 458-461.

M. Pourazad, Z. Moussavi, F. Farahmand, R. Ward. Heart Sounds Separation From Lung Sounds Using Independent Component Analysis. in Proc. Ann. Int. Conf. IEEE EMBS. 2005. pp. 2736-2739.

C. Jen-Chien, H. Ming-Chuan, L. Yue-Der, C. Fokching. “A Study of Heart Sound and Lung Sound Separation by Independent Component Analysis Technique”. in Proc. Ann. Int. Conf. IEEE EMBS. New York City, USA. 2006. pp. 5708-5711.

T. Falk, C. Wai. Modulation filtering for heart and lung sound separation from breath sound recordings. in Proc. Ann. Int. Conf. IEEE EMBS. Vancouvert, Canadá. 2008. pp. 1859-1862.

S. Mallat. A Wavelet Tour of Signal Processing. 3 ed. Ed. Academic Press. San Diego, California, USA. 2009. pp. 299-371.



How to Cite

Salazar, A. J., Alvarado, C., & Lozano, F. E. (2012). System of heart and lung sounds separation for store-and-forward telemedicine applications. Revista Facultad De Ingeniería Universidad De Antioquia, (64), 175–181. Retrieved from