Assessing Transfer Entropy in cardiovascular and respiratory time series under long-range correlations

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Pinto, H (Author) Other; Pernice, R (Author) Other; Amado, C (Author) Other; Maria Eduarda Silva (Author) FEP; Javorka, M (Author) Other; Faes, L (Author) Other; Rocha, AP (Author) FCUP

Conference proceedings International

Title: 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, Mexico, November 1-5, 2021

Pages: 748-751

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 4 Citations

Other information

Authenticus ID: P-00V-ZCM

DOI: 10.1109/embc46164.2021.9630004

Abstract (EN): Heart Period (H) results from the activity of several coexisting control mechanisms, involving Systolic Arterial Pressure (S) and Respiration (R), which operate across multiple time scales encompassing not only short-term dynamics but also long-range correlations. In this work, multiscale representation of Transfer Entropy (TE) and of its decomposition in the network of these three interacting processes is obtained by extending the multivariate approach based on linear parametric VAR models to the Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This approach allows to dissect the different contributions to cardiac dynamics accounting for the simultaneous presence of short and long term dynamics. The proposed method is first tested on simulations of a benchmark VARFI model and then applied to experimental data consisting of H, S and R time series measured in healthy subjects monitored at rest and during mental and postural stress. The results reveal that the proposed method can highlight the dependence of the information transfer on the balance between short-term and long-range correlations in coupled dynamical systems.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 3