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...
Autores principales: | , , , , |
---|---|
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 |