0000000001068069
AUTHOR
R. Cucino
Evaluation of a nonlinear prediction algorithm quantifying regularity, synchronization and directionality in short cardiovascular variability series
An unifying approach evaluating complex dynamics and dynamical interactions in short bivariate time series is presented. The method performs nearest neighbor local linear prediction to estimate regularity, synchronization and directionality of two interacting time series. It was implemented through a specific cross-validation procedure which allowed an unconstrained embedding of the series and a full exploitation of the available data to maximize the accuracy of prediction. The approach was evaluated by simulations of stochastic (autoregressive processes) and deterministic (Henon maps) models in which uncoupled, unidirectionally coupled and bidirectionally coupled dynamics were generated. T…
Exploring causal interactions between blood pressure and RR interval at the respiratory frequency
The mechanisms underlying the relationship between RR interval and systolic arterial pressure (SAP) variability at the respiratory frequency are still object of discussion. In this study, the information on directionality provided by causal cross-spectral analysis was exploited to infer possible influences of respiration on cardiovascular parameters variability. The ability of causal analysis to account for directionality in RR-SAP interrelationships in presence of respiratory exogenous effects was first tested on model simulations. Hence, real data measured on healthy subjects during spontaneous and paced breathing at 0.25 Hz were analysed. The results obtained in real data were consistent…