Robustly separating sound components in human body based on 2-ch ICA and EM algorithm with dirichlet distribution

An algorithm to separate breath sounds (BS), blood stream sounds (BSS), and heart sounds (HS) from sound components in the human body (biosignals) is introduced as a pre-process for detecting circulatory disease such as auricular fibrillation (AF), arteriosclerosis and apnea syndrome. Existing methods in the time-frequency model have been proposed to analyze biosignals with microphone sensors to obtain BS, BSS and HS. However, these methods have negative points. Thus, we propose band pass filter, 2-ch independent component analysis (ICA) and expectation-maximization (EM) algorithm with Dirichlet distribution to solve these problems. Experimental results show that our method performs better than existing methods.