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DaSSWeb - Multivariate and multiscale complexity of linear long-range correlated signals: application in cardiovascular variability

January 4th | 16:00

DaSSWeb, Data Science and Statistics Webinar
Multivariate and multiscale complexity of linear long-range correlated signals: application in cardiovascular variability
Ana Paula Rocha

DM-FCUP & CMUP

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ABSTRACT
An intrinsic feature of some physiological or econometric systems, is their dynamical complexity, resulting from the activity of several coupled mechanisms operating across multiple temporal scales. The cardiovascular system is one of such systems and specific complex characteristics such as long memory and volatility have been considered using an ARFIMA-GARCH approach. Entropy rate is another current measure of complexity. Recently, an efficient estimation of the linear multiscale entropy (MSE) was introduced using a state space formulation. Given the interactions in these systems, natural generalizations consider a multivariate approach with VARFI models. Within this framework, for Gaussian processes, we estimate the Transfer Entropy, or equivalently Granger Causality, allowing to quantify the information flow and assess directed interactions accounting for long-range correlations. The methods are applied in typical experimental and clinical stress situations using cardiovascular signals, and the new measures appear to reflect the changes in the cardiovascular variability system dynamics.

SPEAKER
Ana Paula Rocha is assistant professor at the University of Porto and integrated member of CMUP, where she was principal investigator of the area Signal Processing and Data Analysis in 2005-2014. Her main interests are in interdisciplinary fundamental and applied research in biomedical signals and systems. Author of (> 70) extensive scientific publications has experience in supervising PhDs and Masters (at national and European level), Research Grants and Internships in companies and institutions. Collaborative work in research projects with local Hospitals and research groups from local and EU Universities in the field of Biomedical Statistical Signal Processing and Data Analysis with emphasis in the characterization of cardiovascular variability and risk in stress and critical illness.

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