Effects of a Short-Term Cycling Interval Session and Active Recovery on Non-Linear Dynamics of Cardiac Autonomic Activity in Endurance Trained Cyclists.

Thomas Gronwald,Olaf Hoos,Kuno Hottenrott

doi:10.3390/jcm8020194

Abstract

Measurement of the non-linear dynamics of physiologic variability in a heart rate time series (HRV) provides new opportunities to monitor cardiac autonomic activity during exercise and recovery periods. Using the Detrended Fluctuation Analysis (DFA) technique to assess correlation properties, the present study examines the influence of exercise intensity and recovery on total variability and complexity in the non-linear dynamics of HRV. Sixteen well-trained cyclists performed interval sessions with active recovery periods. During exercise, heart rate (HR) and beat-to-beat (RR)-intervals were recorded continuously. HRV time domain measurements and fractal correlation properties were analyzed using the short-term scaling exponent alpha1 of DFA. Lactate (La) levels and the rate of perceived exertion (RPE) were also recorded at regular time intervals. HR, La, and RPE showed increased values during the interval blocks (p < 0.05). In contrast, meanRR and DFA-alpha1 showed decreased values during the interval blocks (p < 0.05). Also, DFA-alpha1 increased to the level in the warm-up periods during active recovery (p < 0.05) and remained unchanged until the end of active recovery (p = 1.000). The present data verify a decrease in the overall variability, as well as a reduction in the complexity of the RR-interval-fluctuations, owing to increased organismic demands. The acute increase in DFA-alpha1 following intensity-based training stimuli in active recovery may be interpreted as a systematic reorganization of the organism with increased correlation properties in cardiac autonomic activity in endurance trained cyclists.

Highlights

In recent years, analytics conducted with non-linear dynamics and chaos theory have been adapted to gain further insights into the complex cardiovascular regulation and exercise fatigue [1,2]
It was shown that Detrended Fluctuation Analysis (DFA)-alpha1 increased significantly during the active recovery up to the level of the warm-up periods (IB (1) vs. AR (1): p = 0.000; IB (2) vs. AR (3): p = 0.000; IB (3) vs. AR (5): p = 0.000) and remained at nearly the same rate until the end of the active recovery period (AR (1) vs. AR (2): p = 1.000; AR (3) vs. AR (4): p = 1.000; AR (5) vs. AR (6): p = 1.000; Table 1 and Figure 3)
The present data combining interval loads with active recovery periods show that the DFA-alpha1 values return to the level of the warm-up periods very quickly during active recovery and remain at nearly the same values until the end of the active recovery phase in endurance trained cyclists

Summary

Introduction

Analytics conducted with non-linear dynamics and chaos theory have been adapted to gain further insights into the complex cardiovascular regulation and exercise fatigue [1,2]. The present body of research suggests that cardiac dynamics is controlled by complex interactions between the sympathetic and parasympathetic branches of the autonomous nervous system on the sinus node and non-neural factors [3]. These two branches act competitively, resulting in a clear sympathetic activation and parasympathetic withdrawal during exercise [4]. Evaluation of absolute HRV values of time and frequency domain shows that exercise induces diminished variability even at low to moderate exercise intensities Findings derived from such linear parameters have led to inconsistent results during different exercise intensities [4,5]

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