Unsupervised Classification of Heart Sound Recordings

被引:0
|
作者
Tsai, Wei-Ho [1 ]
Su, Sung-How [2 ]
Ma, Cin-Hao [1 ]
机构
[1] Natl Taipei Univ Technol, Grad Inst Comp & Commun Engn, Dept Elect Engn, Taipei 106, Taiwan
[2] Pojen Gen Hosp, Taipei 106, Taiwan
来源
2013 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA) | 2013年
关键词
TRANSFORM; DIAGNOSIS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An unsupervised framework for classifying heart sound data is proposed in this paper. Our goal is to cluster unknown heart sound recordings, such that each cluster contains sound recordings belonging to the same heart diseases or normal heart beat category. This framework is more flexible than the existing supervised classification of heart sounds by the case when heart sound data belong to undefined categories or when there is no prior template data for building a heart sound classifier. To this end, methods are proposed for heart sound feature extraction, similarity computation, cluster generation, and estimation of the optimal number of clusters. Our experiments show that the resulting clusters based on our system are roughly consistent with the heart beat categories defined by human labeling.
引用
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页数:5
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