Identification of the Normal/Abnormal Heart Sounds Based on Energy Features and Xgboost

被引：1
|
作者：
Li, Ting [1 ]
Chen, Xing-rong [1 ]
Tang, Hong [2 ]
Xu, Xiao-ke [1 ]
机构：
[1] Dalian Minzu Univ, Sch Informat & Commun Engn, Dalian, Peoples R China
[2] Dalian Univ Technol, Sch Biomed Engn, Dalian, Peoples R China
来源：
BIOMETRIC RECOGNITION, CCBR 2018 | 2018年 / 10996卷
基金：
中国国家自然科学基金;
关键词：
Heart sounds; Identification; Wavelet packet energy; Xgboost; Feature importance; DIAGNOSIS; SYSTEM;
D O I：
10.1007/978-3-319-97909-0_57
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A normal/abnormal heart sound identification method was put forward in the paper. The wavelet packet energy features of the heart sounds were extracted in a large database of 1136 recordings and xgboost algorithm was used as the classifier. The feature importance is also evaluated and analyzed. Top 3, 6, 9 and 12 features were used to classify the heart sounds. Experimental results showed that the proposed algorithm can identify the normal and abnormal heart sounds effectively. And the result used top 9 features was as good as that of all features, which can reduce almost half of computation.
引用
收藏
页码：536 / 544
页数：9
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