Network analysis of human heartbeat dynamics
Network analysis of human heartbeat dynamics
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DOI：
10.1063/1.3308505
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发表时间：
2010-02-15
影响因子：
4
通讯作者：
Shao, Zhi-Gang
中科院分区：
文献类型：
--
作者：
Shao, Zhi-Gang
我们构建了人类心跳动力学的复杂网络，并研究其统计特性，使用的可见性算法提出的Lacasa和同事[Proc.Natl. Acad. Sci. U.S.A. 105，4972（2008）]。研究结果表明，心跳间隔时间序列的关联网络总是无标度的、高度聚类的、层次结构的和混合的。特别是，关联网络的相关系数可以区分健康受试者和充血性心力衰竭患者。
We construct the complex networks of human heartbeat dynamics and investigate their statistical properties, using the visibility algorithm proposed by Lacasa and co-workers [Proc. Natl. Acad. Sci. U.S.A. 105, 4972 (2008)]. Our results show that the associated networks for the time series of heartbeat interval are always scale-free, high clustering, hierarchy, and assortative mixing. In particular, the assortative coefficient of associated networks could distinguish between healthy subjects and patients with congestive heart failure.