Key result
Cross prediction effectively quantified coupling strength, while predictability improvement elicited the directionality of interactions in short and noisy bivariate time series.
Population
Simulated bivariate time series and physiological data from healthy humans
Comparison
Mutual nonlinear prediction strategies based on… vs Comparison among the three prediction strategies
Design
Other
Authors
Loading...
May aid analysis of noisy HR-BP interactions; leaves open validation before cardiovascular research or clinical use.
This methodological study demonstrates that cross prediction and predictability improvement are effective strategies for evaluating coupling strength and directionality in short, noisy physiological time series like heart rate and blood pressure variability.
Faes et al. (2008) studied healthy humans. Mutual nonlinear prediction strategies was evaluated on Coupling strength and directionality of interactions. Cross prediction effectively quantified coupling strength, while predictability improvement elicited the directionality of interactions in short and noisy bivariate time series.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: