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Monitoring endurance running performance using cardiac parasympathetic function
Martin Buchheit1, A Chivot, J Parouty
1Research Laboratory, EA 3300 "Laboratory of Exercise Physiology and Rehabilitation", Faculty of Sport Sciences, University of Picardie, Jules Verne, 80025 Amiens, France. martin.buchheit@u-picardie.fr
European Journal of Applied Physiology
|December 25, 2009
Summary
This study found that changes in heart rate variability and recovery predict improvements in running performance. These heart rate measures can assess and forecast the effects of aerobic training on endurance runners.
Area of Science:
- Exercise Physiology
- Cardiovascular Regulation
- Sports Science
Background:
- Parasympathetic function influences athletic performance.
- Heart rate variability (HRV) and heart rate recovery (HRR) are key indicators of autonomic function.
- Monitoring these indices can provide insights into training adaptations.
Purpose of the Study:
- To investigate the relationship between running performance and parasympathetic function at rest and post-exercise.
- To analyze changes in heart rate (HR)-derived metrics during an 8-week training program.
- To determine the predictive value of cardiovascular autonomic measures for endurance training outcomes.
Main Methods:
- 14 moderately trained runners participated.
- Resting and post-exercise HRV, exercise HR, and HRR were measured.
- Maximal aerobic speed (MAS) and 10 km running performance were assessed pre- and post-intervention.
- Correlational analyses were performed to link performance changes with autonomic markers.
Main Results:
- Significant correlations were found between changes in vagal indices and improvements in MAS and 10 km running time.
- Exercise HR progressively decreased throughout the training period.
- Responders showed increasing trends in resting vagal indices and post-exercise HRV.
- HRR initially decreased, with smaller changes later in the program.
Conclusions:
- Resting, exercise, and post-exercise heart rate measurements are valuable for assessing training impact.
- These cardiovascular autonomic markers can potentially predict endurance running performance improvements.
- The study highlights the utility of non-invasive HR-derived indices in monitoring training adaptations.
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