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论文类型：期刊论文

发表时间：2012-09-01

发表刊物：BIOMEDICAL SIGNAL PROCESSING AND CONTROL

收录刊物：SCIE、EI、Scopus

卷号：7

期号：5

页面范围：509-516

ISSN号：1746-8094

关键字：Heart sound; Segmentation; Dynamic clustering; Density function; Cycle detection

摘要：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.