A Novel Detection of Ventricular Tachycardia and Fibrillation Based on Degree Centrality of Complex Network

扫码查看

原文链接

NETL
Springer Nature

外文摘要：With the increasing number of cardiovascular disease， some scholars studied it deeply and found that vast majority of sudden cardiac death was due to ventricular fibrillation (VF) or sustained ventricular tachycardia (VT)。 However， they take different treatment measures。 As for patients with VF， we must take defibrillation measure; and patients with VT， we should take low-energy complex heart rate measure。 If we misjudge them， the result would be horrific even taking patients' life。 So in this paper， we put up with a novel detection based on degree centrality of complex network to distinguish the VT and VF signals。 We utilize the characteristics of complex network to analyze the VF and VT signal。 At first， we convert the time series into complex network domain by using horizontal visibility graph。 Then we analyze the complex network and extract the degree centrality as the single feature to classify the VF and VT signals。 Experimental results show that the classification accuracy is up to 99。5%。

外文关键词：

Cardiovascular diseaseVentricular fibrillationVentricular tachycardiaHorizontal visibility graphDegree centrality

作者：

Haihong Liu、Qingfang Meng、Qiang Zhang、Yingda Wei、Mingmin Liu、Hanyong Zhang

展开 >

作者单位：

School of Information Science and Engineering, University of Jinan, Jinan 250022, China,Shandong Provincial Key Laboratory of Network Based Intelligent Computing, Jinan 250022, China

Institute of Jinan Semoconductor Elements Experimentation, Jinan 250014, China

会议名称：

International conference on intelligent computing

会议地点：

Liverpool(GB)

会议母体文献：

Intelligent computing theories and applications

页码：

329-337

出版时间：

2012

DOI：

10.1007/978-3-319-63309-1_30