Medicine and science in sports and exercise · 2026
Fractal Correlation Properties of Heart Rate Variability Differentiates Training Intensity During and After Energy-Matched Cycling Sessions.
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Olieslagers Anton, Müller-Jabusch Yoram, De Maeseneer Jens, Seynaeve Maura, de Beukelaar Toon T
Аннотация
INTRODUCTION/PURPOSE: Recovery optimization requires precise monitoring of physiological stress. This study examines whether detrended fluctuation analysis alpha 1 (DFAa1), a non-linear heart rate variability index, exhibits intensity-dependent responsiveness across energy-matched training sessions in cycling.
METHODS: Nineteen endurance-trained male participants (18-35yrs) completed three equalized workload protocols at different intensities: light (LIGHT), moderate (MOD), and high-intensity interval training (HIIT). Training sessions were matched for energy expenditure by adjusting time via the formula E=P×Δt (E=Energy (J); P=power (W); Δt=time (s)). LIGHT and MOD training were conducted at first and second lactate threshold power (i.e. LT1 and LT2), respectively. HIIT followed a 10x1min protocol at 110% V̇O₂peak power, alternated with 1min rest at 80% LT1 power. Heart Rate (HR) and DFAa1 were assessed throughout the different intensity training sessions as well as during a standardized 10min warm-up (WU) and cool-down (CD) at LT1.
RESULTS: DFAa1 showed apparent stability during LIGHT (p=0.997) and MOD sessions (p=1.000), while showing deterioration during HIIT (p<0.001). On the other hand, HR drift was apparent for all intensities (LIGHT: p=0.003; MOD: p<0.001; HIIT: p<0.001). When directly comparing DFAa1 and HR via ΔZ-scores, a significant effect was found only in MOD (p=0.008). Interestingly, DFAa1 demonstrated significant WU to CD differences for MOD and HIIT (p<0.001), but not for LIGHT (p=0.210), while HR responses showed significant WU to CD differences for all intensities (p<0.001). ΔZ-scores showed significant differences between DFAa1 and HR in MOD (p=0.039) but no significant differences in LIGHT (p=0.098) and HIIT (p=0.071).
CONCLUSIONS: These findings seem to reinforce that DFAa1 holds promise as an objective, system-wide marker of internal workload across varying exercise domains.
METHODS: Nineteen endurance-trained male participants (18-35yrs) completed three equalized workload protocols at different intensities: light (LIGHT), moderate (MOD), and high-intensity interval training (HIIT). Training sessions were matched for energy expenditure by adjusting time via the formula E=P×Δt (E=Energy (J); P=power (W); Δt=time (s)). LIGHT and MOD training were conducted at first and second lactate threshold power (i.e. LT1 and LT2), respectively. HIIT followed a 10x1min protocol at 110% V̇O₂peak power, alternated with 1min rest at 80% LT1 power. Heart Rate (HR) and DFAa1 were assessed throughout the different intensity training sessions as well as during a standardized 10min warm-up (WU) and cool-down (CD) at LT1.
RESULTS: DFAa1 showed apparent stability during LIGHT (p=0.997) and MOD sessions (p=1.000), while showing deterioration during HIIT (p<0.001). On the other hand, HR drift was apparent for all intensities (LIGHT: p=0.003; MOD: p<0.001; HIIT: p<0.001). When directly comparing DFAa1 and HR via ΔZ-scores, a significant effect was found only in MOD (p=0.008). Interestingly, DFAa1 demonstrated significant WU to CD differences for MOD and HIIT (p<0.001), but not for LIGHT (p=0.210), while HR responses showed significant WU to CD differences for all intensities (p<0.001). ΔZ-scores showed significant differences between DFAa1 and HR in MOD (p=0.039) but no significant differences in LIGHT (p=0.098) and HIIT (p=0.071).
CONCLUSIONS: These findings seem to reinforce that DFAa1 holds promise as an objective, system-wide marker of internal workload across varying exercise domains.