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Title: Multivariate and multiscale complexity of long-range correlated cardiovascular variability signals Authors:  Ana Paula Rocha - Univ Porto - Fac Ciencias and CMUP (Portugal) [presenting]
Celestino Amado - Univ Porto - Fac Ciencias (Portugal)
Aurora Martins - CMUP (Portugal)
Maria Eduarda Silva - University of Porto and CIDMA (Portugal)
Abstract: An intrinsic feature of most physiological systems, as well of some climatic or econometric systems, is their dynamical complexity, resulting from the combined activity of several coupled mechanisms typically operating across multiple temporal scales. The cardiovascular system is one of such systems and specific complex characteristics such as long memory have been considered from a model based autoregressive fractionally integrated (ARFI) parametric approach. Entropy rate is another current measure of complexity. Recently, a computationally reliable approach for the practical calculation of the linear multiscale entropy (MSE) of cardiovascular variability signals was introduced. This approach explores a state space formulation and is also able to attend the simultaneous presence of short-term dynamics and long-range correlations by using the ARFI modeling. Moreover, given the interactions present in these systems, it is expectable that a multivariate approach provides enhanced descriptions and a natural generalization considers a multivariate approach with vector ARFI models (VARFI). The methods are applied in some typical experimental/clinical stress situations using cardiovascular signals, and the new measures appear to reflect the changes in the cardiovascular variability system dynamics.