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Analysis of the Atrial Signals Based on a Novel Complex Network

机译:基于新型复杂网络的心房信号分析

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Atrial fibrillation (AF) is one of the most common arrhythmia in clinical, which is the major cause of embolic events and stroke, resulting in an important morbidity and mortality. The mechanisms leading to AF are still under extensive research. In this study, we present a novel complex network approach to analysis the dynamics of the heart during the whole AFprocess (before the AF to end of the AF). Three canine models of acute AF were designed and the common parameters of the novel complex network were used to investigate the method. The results show that the novel complex network parameter can not only detect the AF, but also can estimate the vulnerability of atrialfibrillation effectively.
机译:心房颤动(AF)是临床中最常见的心律失常之一,这是栓塞事件和中风的主要原因,导致了一个重要的发病率和死亡率。通往AF的机制仍在进行广泛的研究下。在这项研究中,我们提出了一种新的复杂网络方法来分析整个Afprocess(在AF的AF之前)中心脏的动态。设计了三个犬型AF的模型,并使用了新型复杂网络的共同参数来研究该方法。结果表明,新颖的复杂网络参数不仅可以检测到AF,还可以有效地估算故障频率的脆弱性。

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