Dynamical heart beat correlations during running

Abstract Fluctuations of the human heart beat constitute a complex system that has been studied mostly under resting conditions using conventional time series analysis methods. During physical exercise, the variability of the fluctuations is reduced, and the time series of beat-to-beat RR intervals...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Matti Molkkari, Giorgio Angelotti, Thorsten Emig, Esa Räsänen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f3e6efab35934413a9a0ac5f2913ed3a
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:f3e6efab35934413a9a0ac5f2913ed3a
record_format	dspace
spelling	oai:doaj.org-article:f3e6efab35934413a9a0ac5f2913ed3a2021-12-02T18:50:55ZDynamical heart beat correlations during running10.1038/s41598-020-70358-72045-2322https://doaj.org/article/f3e6efab35934413a9a0ac5f2913ed3a2020-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-70358-7https://doaj.org/toc/2045-2322Abstract Fluctuations of the human heart beat constitute a complex system that has been studied mostly under resting conditions using conventional time series analysis methods. During physical exercise, the variability of the fluctuations is reduced, and the time series of beat-to-beat RR intervals (RRIs) become highly non-stationary. Here we develop a dynamical approach to analyze the time evolution of RRI correlations in running across various training and racing events under real-world conditions. In particular, we introduce dynamical detrended fluctuation analysis and dynamical partial autocorrelation functions, which are able to detect real-time changes in the scaling and correlations of the RRIs as functions of the scale and the lag. We relate these changes to the exercise intensity quantified by the heart rate (HR). Beyond subject-specific HR thresholds the RRIs show multiscale anticorrelations with both universal and individual scale-dependent structure that is potentially affected by the stride frequency. These preliminary results are encouraging for future applications of the dynamical statistical analysis in exercise physiology and cardiology, and the presented methodology is also applicable across various disciplines.Matti MolkkariGiorgio AngelottiThorsten EmigEsa RäsänenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Matti Molkkari Giorgio Angelotti Thorsten Emig Esa Räsänen Dynamical heart beat correlations during running
description	Abstract Fluctuations of the human heart beat constitute a complex system that has been studied mostly under resting conditions using conventional time series analysis methods. During physical exercise, the variability of the fluctuations is reduced, and the time series of beat-to-beat RR intervals (RRIs) become highly non-stationary. Here we develop a dynamical approach to analyze the time evolution of RRI correlations in running across various training and racing events under real-world conditions. In particular, we introduce dynamical detrended fluctuation analysis and dynamical partial autocorrelation functions, which are able to detect real-time changes in the scaling and correlations of the RRIs as functions of the scale and the lag. We relate these changes to the exercise intensity quantified by the heart rate (HR). Beyond subject-specific HR thresholds the RRIs show multiscale anticorrelations with both universal and individual scale-dependent structure that is potentially affected by the stride frequency. These preliminary results are encouraging for future applications of the dynamical statistical analysis in exercise physiology and cardiology, and the presented methodology is also applicable across various disciplines.
format	article
author	Matti Molkkari Giorgio Angelotti Thorsten Emig Esa Räsänen
author_facet	Matti Molkkari Giorgio Angelotti Thorsten Emig Esa Räsänen
author_sort	Matti Molkkari
title	Dynamical heart beat correlations during running
title_short	Dynamical heart beat correlations during running
title_full	Dynamical heart beat correlations during running
title_fullStr	Dynamical heart beat correlations during running
title_full_unstemmed	Dynamical heart beat correlations during running
title_sort	dynamical heart beat correlations during running
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/f3e6efab35934413a9a0ac5f2913ed3a
work_keys_str_mv	AT mattimolkkari dynamicalheartbeatcorrelationsduringrunning AT giorgioangelotti dynamicalheartbeatcorrelationsduringrunning AT thorstenemig dynamicalheartbeatcorrelationsduringrunning AT esarasanen dynamicalheartbeatcorrelationsduringrunning
_version_	1718377481003597824

Dynamical heart beat correlations during running

Ejemplares similares