Parallel source separation system for heart and lung sounds

摘要

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.