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Open AccessArticle

Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study

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Faculty of Technical Sciences-DEET, University of Novi Sad, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia
2
Faculty of Dental Medicine, University of Belgrade, Dr. Subotica 1, 11000 Belgrade, Serbia
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School of Medicine, University of Belgrade, Dr. Subotica 1, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(11), 1103; https://doi.org/10.3390/e21111103
Received: 15 August 2019 / Revised: 8 November 2019 / Accepted: 9 November 2019 / Published: 11 November 2019
(This article belongs to the Special Issue Multiscale Entropy Approaches and Their Applications)
This paper proposes a method that maps the coupling strength of an arbitrary number of signals D, D ≥ 2, into a single time series. It is motivated by the inability of multiscale entropy to jointly analyze more than two signals. The coupling strength is determined using the copula density defined over a [0 1]D copula domain. The copula domain is decomposed into the Voronoi regions, with volumes inversely proportional to the dependency level (coupling strength) of the observed joint signals. A stream of dependency levels, ordered in time, creates a new time series that shows the fluctuation of the signals’ coupling strength along the time axis. The composite multiscale entropy (CMSE) is then applied to three signals, systolic blood pressure (SBP), pulse interval (PI), and body temperature (tB), simultaneously recorded from rats exposed to different ambient temperatures (tA). The obtained results are consistent with the results from the classical studies, and the method itself offers more levels of freedom than the classical analysis. View Full-Text
Keywords: copula density; dependency structures; Voronoi decomposition; multiscale entropy; ambient temperature; telemetry; systolic blood pressure; pulse interval; thermoregulation; vasopressin copula density; dependency structures; Voronoi decomposition; multiscale entropy; ambient temperature; telemetry; systolic blood pressure; pulse interval; thermoregulation; vasopressin
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Bajic, D.; Skoric, T.; Milutinovic-Smiljanic, S.; Japundzic-Zigon, N. Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study. Entropy 2019, 21, 1103.

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