Key result
Running elicits intensity-dependent RR interval anticorrelations above a subject-specific heart rate threshold.
Why the study?
Fluctuations of the human heart beat have been studied mostly under resting conditions, whereas during physical exercise variability is reduced and RR intervals become highly non-stationary.
Observational (n=19)
Dynamic detrended fluctuation analysis reveals that heart beat intervals exhibit multiscale anticorrelations during running that depend on exercise intensity and subject-specific heart rate thresholds.
Approach enables RRI correlation tracking during real-world running; leaves open clinical validation and utility in disease.
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.
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A 2020 study conducted an observational in Healthy runners (n=19). Running exercise vs. Rest or lower intensity exercise was evaluated on Dynamic scale-dependent scaling exponent α(t, s) and dynamic partial autocorrelation function (DPACF) of RR intervals. During running, beat-to-beat RR intervals exhibit multiscale anticorrelations that emerge after heart rate exceeds a subject-specific threshold and vary with exercise intensity.
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