Multiscale ordinal network analysis of human cardiac dynamics

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
M McCulloughT Stemler

Abstract

In this study, we propose a new information theoretic measure to quantify the complexity of biological systems based on time-series data. We demonstrate the potential of our method using two distinct applications to human cardiac dynamics. Firstly, we show that the method clearly discriminates between segments of electrocardiogram records characterized by normal sinus rhythm, ventricular tachycardia and ventricular fibrillation. Secondly, we investigate the multiscale complexity of cardiac dynamics with respect to age in healthy individuals using interbeat interval time series and compare our findings with a previous study which established a link between age and fractal-like long-range correlations. The method we use is an extension of the symbolic mapping procedure originally proposed for permutation entropy. We build a Markov chain of the dynamics based on order patterns in the time series which we call an ordinal network, and from this model compute an intuitive entropic measure of transitional complexity. A discussion of the model parameter space in terms of traditional time delay embedding provides a theoretical basis for our multiscale approach. As an ancillary discussion, we address the practical issue of node aliasing ...Continue Reading

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Citations

Nov 28, 2019·Physical Review. E·Arthur A B Pessa, Haroldo V Ribeiro
May 17, 2017·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·José M Amigó, Michael Small
Jan 23, 2020·Physical Review. E·Konstantinos SakellariouMichael Small
Dec 18, 2020·Physical Review. E·Arthur A B Pessa, Haroldo V Ribeiro
Mar 20, 2021·Physical Review. E·Konstantinos SakellariouMichael Small
May 28, 2021·Cognitive Neurodynamics·Zhongke GaoMatjaž Perc

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