Segmentation of heart sounds based on dynamic clustering

Title
Segmentation of heart sounds based on dynamic clustering
Author(s)
박용완탕홍[탕홍]리팅[리팅]추찬성[추찬성]
Keywords
PULMONARY COMPONENTS; ALGORITHM; SIGNAL; MODEL; CLASSIFICATION
Issue Date
201209
Publisher
ELSEVIER SCI LTD
Citation
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, v.7, no.5, pp.509 - 516
Abstract
The heart sound signal is first separated into cycles, where the cycle detection is based on an instantaneous cycle frequency. The heart sound data of one cardiac cycle can be decomposed into a number of atoms characterized by timing delay, frequency, amplitude, time width and phase. To segment heart sounds, we made a hypothesis that the atoms of a heart sound congregate as a cluster in time-frequency domains. We propose an atom density function to indicate clusters. To suppress clusters of murmurs and noise, weighted density function by atom energy is further proposed to improve the segmentation of heart sounds. Therefore, heart sounds are indicated by the hybrid analysis of clustering and medical knowledge. The segmentation scheme is automatic and no reference signal is needed. Twenty-six subjects, including 3 normal and 23 abnormal subjects, were tested for heart sound signals in various clinical cases. Our statistics show that the segmentation was successful for signals collected from normal subjects and patients with moderate murmurs. (C) 2011 Elsevier Ltd. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/27360http://dx.doi.org/10.1016/j.bspc.2011.09.002
ISSN
1746-8094
Appears in Collections:
공과대학 > 모바일정보통신공학과 > Articles
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