Classical Poincaré plot is a standard way to measure nonlinear regulation of cardiovascular control. In our work we propose a generalized form of Poincaré plot where we track correlation between the duration of j preceding and k next RR intervals. The investigation was done in healthy subjects and patients with atrial fibrillation, by varying j,k ≤ 100. In cases where j = k, in healthy subjects the typical pattern was observed by "paths" that were substituting scatterplots and that were initiated and ended by loops of Poincaré plot points. This was not the case for atrial fibrillation patients where Poincaré plot had a simple scattered form. More, a typical matrix of Pearson's correlation coefficients, r(j,k), showed different positions of local maxima, depending on the subject's health condition. In both groups, local maxima were grouped into four clusters which probably determined specific regulatory mechanisms according to correlations between the duration of symmetric and asymmetric observed RR intervals. We quantified matrices' degrees of asymmetry and found that they were significantly different: distributed around zero in healthy, while being negative in atrial fibrillation. Also, Pearson's coefficients were higher in healthy than in atrial fibrillation or in signals with reshuffled intervals. Our hypothesis is that by this novel method we can observe heart rate regimes typical for baseline conditions and "defense reaction" in healthy subjects. These data indicate that neural control mechanisms of heart rate are operating in healthy subjects in contrast with atrial fibrillation, identifying it as the state of risk for stress-dependent pathologies. Regulatory regimes of heart rate can be further quantified and explored by the proposed novel method.
Keywords: Poincaré plot; atrial fibrillation; autonomic nervous system; heart rate; indexes of asymmetry; neural control regimes.