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Authors: Nicolò Pini 1 ; Maristella Lucchini 1 ; William Fifer 2 ; Nina Burtchen 3 and Maria Signorini 4

Affiliations: 1 Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy, Department of Psychiatry, Columbia University College of Physicians & Surgeons, 10032 New York and U.S.A. ; 2 Department of Psychiatry, Columbia University College of Physicians & Surgeons, 10032 New York and U.S.A. ; 3 Department of Psychosomatic Medicine and Psychotherapy, University of Freiburg, 79106 Freiburg and Germany ; 4 Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano and Italy

ISBN: 978-989-758-353-7

ISSN: 2184-4305

Keyword(s): Transfer Entropy, Cardiorespiratory Regulation, Multivariate Modelling, Sleep Regulation, Autonomic Nervous System.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Cardiovascular Signals ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: The autonomic nervous system (ANS) acts modulating the cardiac and respiratory systems by means of the sympathetic and parasympathetic branches. In this work, we propose to employ Transfer Entropy (TE) with the aim of disambiguating the contributions of the two branches over cardiorespiratory regulation in newborns during sleep. Specifically, we computed TE on the original time series representative of the two subsystems, namely Heart Rate Variability (HRV) and Respiration (RESP). Furthermore, we employed a lagged version of the two original signals to derive a TE estimation capable of providing and insight on the short-term memory between the two systems. Results show the information transfer quantified by TERESP→RR decaying rapidly as the shift between the two time series increases. On the other hand, TERR→RESP exhibits a slower but prolonged interaction, which lasts over numerous lags. The novel approach presented in this work affords the potential to assess infants’ ANS developmen t in terms of the quantification of cardiorespiratory control functioning. (More)

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Paper citation in several formats:
Pini, N.; Lucchini, M.; Fifer, W.; Burtchen, N. and Signorini, M. (2019). Lagged Transfer Entropy Analysis to Investigate Cardiorespiratory Regulation in Newborns during Sleep.In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4 BIOSIGNALS: BIOSIGNALS, ISBN 978-989-758-353-7, ISSN 2184-4305, pages 139-146. DOI: 10.5220/0007363301390146

@conference{biosignals19,
author={Nicolò Pini. and Maristella Lucchini. and William P. Fifer. and Nina Burtchen. and Maria G. Signorini.},
title={Lagged Transfer Entropy Analysis to Investigate Cardiorespiratory Regulation in Newborns during Sleep},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4 BIOSIGNALS: BIOSIGNALS,},
year={2019},
pages={139-146},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007363301390146},
isbn={978-989-758-353-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4 BIOSIGNALS: BIOSIGNALS,
TI - Lagged Transfer Entropy Analysis to Investigate Cardiorespiratory Regulation in Newborns during Sleep
SN - 978-989-758-353-7
AU - Pini, N.
AU - Lucchini, M.
AU - Fifer, W.
AU - Burtchen, N.
AU - Signorini, M.
PY - 2019
SP - 139
EP - 146
DO - 10.5220/0007363301390146

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