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Open AccessArticle

Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling

1
Institute of Biophysics, Faculty of Medicine, University of Belgrade, KCS, PO Box 22, 11129 Belgrade, Serbia
2
Pacemaker Center, Clinical Center of Serbia, 11000 Belgrade, Serbia
3
Department for Life Sciences, Institute for Multidisciplinary Research, University of Belgrade, 11000 Belgrade, Serbia
4
Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(9), 1042; https://doi.org/10.3390/e22091042
Received: 16 July 2020 / Revised: 30 July 2020 / Accepted: 14 August 2020 / Published: 18 September 2020
(This article belongs to the Special Issue Entropy in Data Analysis)
It is known that in pathological conditions, physiological systems develop changes in the multiscale properties of physiological signals. However, in real life, little is known about how changes in the function of one of the two coupled physiological systems induce changes in function of the other one, especially on their multiscale behavior. Hence, in this work we aimed to examine the complexity of cardio-respiratory coupled systems control using multiscale entropy (MSE) analysis of cardiac intervals MSE (RR), respiratory time series MSE (Resp), and synchrony of these rhythms by cross multiscale entropy (CMSE) analysis, in the heart failure (HF) patients and healthy subjects. We analyzed 20 min of synchronously recorded RR intervals and respiratory signal during relaxation in the supine position in 42 heart failure patients and 14 control healthy subjects. Heart failure group was divided into three subgroups, according to the RR interval time series characteristics (atrial fibrillation (HFAF), sinus rhythm (HFSin), and sinus rhythm with ventricular extrasystoles (HFVES)). Compared with healthy control subjects, alterations in respiratory signal properties were observed in patients from the HFSin and HFVES groups. Further, mean MSE curves of RR intervals and respiratory signal were not statistically different only in the HFSin group (p = 0.43). The level of synchrony between these time series was significantly higher in HFSin and HFVES patients than in control subjects and HFAF patients (p < 0.01). In conclusion, depending on the specific pathologies, primary alterations in the regularity of cardiac rhythm resulted in changes in the regularity of the respiratory rhythm, as well as in the level of their asynchrony. View Full-Text
Keywords: cross multiscale entropy analysis; sample entropy; cardiopulmonary coupling; heart rhythm; respiratory rhythm; heart failure; atrial fibrillation; sinus rhythm; sinus rhythm with ventricular extrasystoles; autonomic nervous system cross multiscale entropy analysis; sample entropy; cardiopulmonary coupling; heart rhythm; respiratory rhythm; heart failure; atrial fibrillation; sinus rhythm; sinus rhythm with ventricular extrasystoles; autonomic nervous system
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MDPI and ACS Style

Platiša, M.M.; Radovanović, N.N.; Kalauzi, A.; Milašinović, G.; Pavlović, S.U. Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling. Entropy 2020, 22, 1042. https://doi.org/10.3390/e22091042

AMA Style

Platiša MM, Radovanović NN, Kalauzi A, Milašinović G, Pavlović SU. Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling. Entropy. 2020; 22(9):1042. https://doi.org/10.3390/e22091042

Chicago/Turabian Style

Platiša, Mirjana M.; Radovanović, Nikola N.; Kalauzi, Aleksandar; Milašinović, Goran; Pavlović, Siniša U. 2020. "Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling" Entropy 22, no. 9: 1042. https://doi.org/10.3390/e22091042

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