A dynamic marker of very short-term heartbeat under pathological states via network analysis
1 School of Science, China Pharmaceutical University - Nanjing 210009, China
2 School of Geographic and Biological Information, Nanjing University of Posts and Telecommunications Nanjing 210003, China
Received: 22 July 2014
Accepted: 6 August 2014
We developed a novel network to probe pathological states with the aid of heartbeat time series, by regarding each vector in the embedding phase space as one node of the network and using a permutation-based measure to determine links between nodes. The entropy of the degree distribution of the network shows a general and significant reduction under pathological conditions, even when there are only ultra short-term heartbeats available. The reduction of is possibly a dynamic marker of cardiac disorders. Our results reveal that a comparatively strong “memory” should usually exist in the healthy cardiovascular system whereas it dramatically declines when a cardiac disease is arising. The proposed method shows great promise in screening cardiac diseases and monitoring dynamic changes of the autonomic nervous system. Besides, as a universal method for analyzing the time series, the proposed approach seems to be promising also for other research disciplines.
PACS: 87.19.Hh – Cardiac dynamics / 05.45.Tp – Time series analysis / 05.10.-a – Computational methods in statistical physics and nonlinear dynamics
© EPLA, 2014