To fully elucidate the complex physiological mechanisms underlying the short-term autonomic regulation of heart period (H), systolic and diastolic arterial pressure (S, D) and respiratory (R) variability, the joint dynamics of these variables need to be explored using multivariate time series analysis. This study proposes the utilization of information-theoretic measures to measure causal interactions between nodes of the cardiovascular/cardiorespiratory network and to assess the nature (synergistic or redundant) of these directed interactions. Indexes of information transfer and information modification are extracted from the H, S, D and R series measured from healthy subjects in a resting state and during postural stress. Computations are performed in the framework of multivariate linear regression, using bootstrap techniques to assess on a single-subject basis the statistical significance of each measure and of its transitions across conditions. We find patterns of information transfer and modification which are related to specific cardiovascular and cardiorespiratory mechanisms in resting conditions and to their modification induced by the orthostatic stress.

Faes, L., Nollo, G., Krohova, J., Czippelova, B., Turianikova, Z., Javorka, M. (2017). Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 1563-1566). Institute of Electrical and Electronics Engineers Inc. [10.1109/EMBC.2017.8037135].

Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks

Faes, Luca
;
2017-01-01

Abstract

To fully elucidate the complex physiological mechanisms underlying the short-term autonomic regulation of heart period (H), systolic and diastolic arterial pressure (S, D) and respiratory (R) variability, the joint dynamics of these variables need to be explored using multivariate time series analysis. This study proposes the utilization of information-theoretic measures to measure causal interactions between nodes of the cardiovascular/cardiorespiratory network and to assess the nature (synergistic or redundant) of these directed interactions. Indexes of information transfer and information modification are extracted from the H, S, D and R series measured from healthy subjects in a resting state and during postural stress. Computations are performed in the framework of multivariate linear regression, using bootstrap techniques to assess on a single-subject basis the statistical significance of each measure and of its transitions across conditions. We find patterns of information transfer and modification which are related to specific cardiovascular and cardiorespiratory mechanisms in resting conditions and to their modification induced by the orthostatic stress.
2017
Settore ING-INF/06 - Bioingegneria Elettronica E Informatica
9781509028092
Faes, L., Nollo, G., Krohova, J., Czippelova, B., Turianikova, Z., Javorka, M. (2017). Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 1563-1566). Institute of Electrical and Electronics Engineers Inc. [10.1109/EMBC.2017.8037135].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/271769
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