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

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6 Author(s)
Hashiodani, K. ; Sci. & Eng., Ritsumeikan Univ., Kusatsu, Japan ; Takada, S. ; Fukumizu, Y. ; Yamauchi, H.
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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.

Published in:

Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on

Date of Conference:

5-7 Jan. 2012

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