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基于联合熵的室性心动过速和心室颤动检测

[Detection of ventricular tachycardia and ventricular fibrillation based on joint entropy].

作者信息

Chen Jie, Wang Jun

机构信息

Image Processing and Image Communications Key Lab., College of Telecommunications & Information Engineering, Nanjing Univ. of Posts & Telecomm., Nanjing 210003, China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2010 Feb;27(1):24-7.

Abstract

This is a research with the aim of using joint entropy method to analyze the dynamical complexity information on the electrocardiogram signals recording of normal sinus rhythm (NSR), ventricular tachycardia (VT) and ventricular fibrillation (VF). We included the symbolic dynamical theory and surrogate data concept in it. By calculating the joint entropy between original and surrogate time series, we quantified the dynamical complexity of original series. By computer analysis of actual heartbeat rhythm data, the rationality of joint entropy method was confirmed. The results indicated that the joint entropy values of different signals can be of use in distinguishing the NSR, VT and VF signals.

摘要

这是一项旨在运用联合熵方法分析正常窦性心律(NSR)、室性心动过速(VT)和心室颤动(VF)心电图信号记录中的动态复杂性信息的研究。我们将符号动力学理论和替代数据概念纳入其中。通过计算原始时间序列与替代时间序列之间的联合熵,我们对原始序列的动态复杂性进行了量化。通过对实际心跳节律数据的计算机分析,证实了联合熵方法的合理性。结果表明,不同信号的联合熵值可用于区分NSR、VT和VF信号。

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Multifractal analysis of ventricular fibrillation and ventricular tachycardia.心室颤动和室性心动过速的多重分形分析
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