The BCG signal feature extraction and recognition based on the cumulative residual entropy

被引：0

作者：

Ma, Zhixin ^{[1
]}

Chu, Taishan ^{[1
]}

机构：

[1] Natl Engn Res Ctr Broadband Networks & Applicat, Shanghai, Peoples R China

来源：

2013 2ND INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND MEASUREMENT, SENSOR NETWORK AND AUTOMATION (IMSNA) | 2013年

关键词：

cumulative residual entropy; Ballistocardiogram (BCG); Support Vector Machine (SVM); Disease Identification; obstructive sleep apnea-hypopnea syndrome (OSAHS); Arrhythmia;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

in this paper, we use cumulative residual entropy to get the features of Ballistocardiogram (BCG). The data after feature recognition are classified by Support Vector Machine (SVM) algorithm to compare the accuracy. Experimental results indicate that high classification accuracy can be obtained. The method can be used in some disease identification.

引用

页码：526 / 528

页数：3

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