Cargando…

Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling

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 o...

Descripción completa

Detalles Bibliográficos
Autores principales: Platiša, Mirjana M., Radovanović, Nikola N., Kalauzi, Aleksandar, Milašinović, Goran, Pavlović, Siniša U.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597100/
https://www.ncbi.nlm.nih.gov/pubmed/33286811
http://dx.doi.org/10.3390/e22091042
_version_ 1783602261440593920
author Platiša, Mirjana M.
Radovanović, Nikola N.
Kalauzi, Aleksandar
Milašinović, Goran
Pavlović, Siniša U.
author_facet Platiša, Mirjana M.
Radovanović, Nikola N.
Kalauzi, Aleksandar
Milašinović, Goran
Pavlović, Siniša U.
author_sort Platiša, Mirjana M.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7597100
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75971002020-11-09 Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling Platiša, Mirjana M. Radovanović, Nikola N. Kalauzi, Aleksandar Milašinović, Goran Pavlović, Siniša U. Entropy (Basel) Article 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. MDPI 2020-09-18 /pmc/articles/PMC7597100/ /pubmed/33286811 http://dx.doi.org/10.3390/e22091042 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Platiša, Mirjana M.
Radovanović, Nikola N.
Kalauzi, Aleksandar
Milašinović, Goran
Pavlović, Siniša U.
Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title_full Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title_fullStr Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title_full_unstemmed Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title_short Multiscale Entropy Analysis: Application to Cardio-Respiratory Coupling
title_sort multiscale entropy analysis: application to cardio-respiratory coupling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597100/
https://www.ncbi.nlm.nih.gov/pubmed/33286811
http://dx.doi.org/10.3390/e22091042
work_keys_str_mv AT platisamirjanam multiscaleentropyanalysisapplicationtocardiorespiratorycoupling
AT radovanovicnikolan multiscaleentropyanalysisapplicationtocardiorespiratorycoupling
AT kalauzialeksandar multiscaleentropyanalysisapplicationtocardiorespiratorycoupling
AT milasinovicgoran multiscaleentropyanalysisapplicationtocardiorespiratorycoupling
AT pavlovicsinisau multiscaleentropyanalysisapplicationtocardiorespiratorycoupling