Using nonlocal means to separate cardiac and respiration sounds

The paper presents the results of applying nonlocal means (NLMs) approach in the problem of separating respiration and cardiac sounds in a signal recorded on a human chest wall. The performance of the algorithm was tested both by simulated and real signals. As a quantitative efficiency measure of NLM filtration, the angle of divergence between isolated and reference signal was used. It is shown that for a wide range of signal-to-noise ratios, the algorithm makes it possible to efficiently solve this problem of separating cardiac and respiration sounds in the sum signal recorded on a human chest wall.