TY  - JOUR
AU  - Bajić, Dragana
AU  - Skorić, Tamara
AU  - Milutinović-Smiljanić, Sanja
AU  - Japundžić-Žigon, Nina
PY  - 2019
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2418
AB  - 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 (t(B)), simultaneously recorded from rats exposed to different ambient temperatures (t(A)). 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.
PB  - Mdpi, Basel
T2  - Entropy
T1  - Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study
VL  - 21
IS  - 11
DO  - 10.3390/e21111103
ER  - 

@article{
author = "Bajić, Dragana and Skorić, Tamara and Milutinović-Smiljanić, Sanja and Japundžić-Žigon, Nina",
year = "2019",
abstract = "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 (t(B)), simultaneously recorded from rats exposed to different ambient temperatures (t(A)). 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.",
publisher = "Mdpi, Basel",
journal = "Entropy",
title = "Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study",
volume = "21",
number = "11",
doi = "10.3390/e21111103"
}

Bajić, D., Skorić, T., Milutinović-Smiljanić, S.,& Japundžić-Žigon, N.. (2019). Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study. in Entropy
Mdpi, Basel., 21(11).
https://doi.org/10.3390/e21111103

Bajić D, Skorić T, Milutinović-Smiljanić S, Japundžić-Žigon N. Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study. in Entropy. 2019;21(11).
doi:10.3390/e21111103 .

Bajić, Dragana, Skorić, Tamara, Milutinović-Smiljanić, Sanja, Japundžić-Žigon, Nina, "Voronoi Decomposition of Cardiovascular Dependency Structures in Different Ambient Conditions: An Entropy Study" in Entropy, 21, no. 11 (2019),
https://doi.org/10.3390/e21111103 . .