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Dynamical heart beat correlations during running

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Dynamical heart beat correlations during running. / Molkkari, Matti; Angelotti, Giorgio; Emig, Thorsten; Räsänen, Esa.

In: Scientific Reports, Vol. 10, No. 1, 13627, 2020.

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Molkkari, Matti ; Angelotti, Giorgio ; Emig, Thorsten ; Räsänen, Esa. / Dynamical heart beat correlations during running. In: Scientific Reports. 2020 ; Vol. 10, No. 1.

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@article{ddf0e2a6fd244f5fb9de7712a5a9bae6,
title = "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 (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.",
author = "Matti Molkkari and Giorgio Angelotti and Thorsten Emig and Esa R{\"a}s{\"a}nen",
year = "2020",
doi = "10.1038/s41598-020-70358-7",
language = "English",
volume = "10",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",

}

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TY - JOUR

T1 - Dynamical heart beat correlations during running

AU - Molkkari, Matti

AU - Angelotti, Giorgio

AU - Emig, Thorsten

AU - Räsänen, Esa

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

U2 - 10.1038/s41598-020-70358-7

DO - 10.1038/s41598-020-70358-7

M3 - Article

VL - 10

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 13627

ER -