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Parallel source separation system for heart and lung sounds

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Abstract

In this paper, we propose a parallel source separation system designed to extract heart and lung sounds from single-channel mixtures. The proposed system is based on a non-negative matrix factorization (NMF) approach and a clustering strategy together with a soft-masking filtering. Furthermore, we propose an offline and online implementation of the framework which can be applied in many real-time scenarios, such as the extraction of clinical parameters, remote auscultation and breath sound analysis. Experimental results show that it is possible to achieve fast execution times, which enable a real-time behavior, combining parallel and high-performance techniques.

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Acknowledgements

This work was supported by the Regional Ministry of the Principality of Asturias under Grant FC-GRUPIN-IDI/2018/000226, by the Ministry of Economy, Knowledge and University of the Government of the Junta de Andalucía under Project P18-RT-1994 and by the “Programa Operativo FEDER Andalucía 2014-2020” under Project with Reference 1257914.

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Authors and Affiliations

  1. Department of Telecommunication Engineering, Universidad de Jaén, Jaén, Spain

    A. J. Muñoz-Montoro & F. J. Canadas-Quesada

  2. Department of Computer Science, Universidad de Oviedo, Oviedo, Spain

    D. Suarez-Dou, R. Cortina & E. F. Combarro

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  1. A. J. Muñoz-Montoro
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  2. D. Suarez-Dou
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  3. R. Cortina
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  4. F. J. Canadas-Quesada
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  5. E. F. Combarro
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Correspondence to A. J. Muñoz-Montoro.

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Muñoz-Montoro, A.J., Suarez-Dou, D., Cortina, R. et al. Parallel source separation system for heart and lung sounds. J Supercomput 77, 8135–8150 (2021). https://doi.org/10.1007/s11227-020-03616-0

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