Computation of Nonlinear Parameters of Heart Rhythm Using Short Time ECG Segments

We propose the method to compute the nonlinear parameters of heart rhythm (correlation dimension D (2) and correlation entropy K (2)) using 5-minute ECG recordings preferred for screening of population. Conversion of RR intervals' time series into continuous function x(t) allows getting the new time series with different sampling rate dt. It has been shown that for all dt (250, 200, 125, and 100 ms) the cross-plots of D (2) and K (2) against embedding dimension m for phase-space reconstruction start to level off at m = 9. The sample size N at different sampling rates varied from 1200 at dt = 250 ms to 3000 at dt = 100 ms. Along with, the D (2) and K (2) means were not statistically different; that is, the sampling rate did not influence the results. We tested the feasibility of the method in two models: nonlinear heart rhythm dynamics in different states of autonomous nervous system and age-related characteristics of nonlinear parameters. According to the acquired data, the heart rhythm is more complex in childhood and adolescence with more influential parasympathetic influence against the background of elevated activity of sympathetic autonomous nervous system.