Gianluca Vernillo1, Gregory Doucende2, Johan Cassirame3, Laurent Mourot4. 1. Department of Biomedical Sciences for Health, Università degli Studi di Milano, Italy; Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Canada. Electronic address: gianluca.vernillo@gmail.com. 2. Université de Perpignan Via Domitia, Laboratoire Européen Performance Santé Altitude (LEPSA), France. 3. Laboratoire Culture, Sport, Santé et Société, Exercise and Performance Health Innovation (EPHI) platform, Université Bourgogne-Franche Comté, France. 4. EA3920 Prognostic Factors and Regulatory Factors of Cardiac and Vascular Pathologies, Exercise Performance Health Innovation (EPHI) platform, University of Bourgogne Franche-Comté, France; Tomsk Polytechnic University, Russia.
Abstract
OBJECTIVES: At a given running speed, humans naturally endeavor to achieve an optimal stride frequency that minimizes metabolic cost. Research has suggested that runners select this near optimal stride frequency in some process of self-optimization even during fatiguing tasks up to 1-h of high-intensity running. Here, we studied whether runners demonstrate a similar self-optimizing capability after an ultramarathon of 6 h. DESIGN: Controlled pre-post study. METHOD: We collected temporal stride kinematics and metabolic data in nine (experimental group) male runners before and after 6 h of running and in six (control group) male ultramarathon runners who did not run, but stayed awake and performed normal, daily physical activities avoiding strenuous exercises over the 6-h period. For each participant, preferred and optimal stride frequencies were measured, where stride frequency was systematically varied above and below PSF (±4% and ±8%). RESULTS: Preferred and optimal stride frequencies across time and group showed no significant differences (p ≥ 0.276). Furthermore, neither the overall relationship between metabolic cost and stride frequency, nor the energetically optimal stride frequency changed substantially after several hours of running. CONCLUSIONS: Similar dynamics of stride frequency adjustments in the experimental group occurred as those found in a non-fatigued state. This suggests that after an ultramarathon of 6 h, runners were still able to optimize their gait, and automatically adjust it in order to converge on the energetically optimal gait.
OBJECTIVES: At a given running speed, humans naturally endeavor to achieve an optimal stride frequency that minimizes metabolic cost. Research has suggested that runners select this near optimal stride frequency in some process of self-optimization even during fatiguing tasks up to 1-h of high-intensity running. Here, we studied whether runners demonstrate a similar self-optimizing capability after an ultramarathon of 6 h. DESIGN: Controlled pre-post study. METHOD: We collected temporal stride kinematics and metabolic data in nine (experimental group) male runners before and after 6 h of running and in six (control group) male ultramarathon runners who did not run, but stayed awake and performed normal, daily physical activities avoiding strenuous exercises over the 6-h period. For each participant, preferred and optimal stride frequencies were measured, where stride frequency was systematically varied above and below PSF (±4% and ±8%). RESULTS: Preferred and optimal stride frequencies across time and group showed no significant differences (p ≥ 0.276). Furthermore, neither the overall relationship between metabolic cost and stride frequency, nor the energetically optimal stride frequency changed substantially after several hours of running. CONCLUSIONS: Similar dynamics of stride frequency adjustments in the experimental group occurred as those found in a non-fatigued state. This suggests that after an ultramarathon of 6 h, runners were still able to optimize their gait, and automatically adjust it in order to converge on the energetically optimal gait.
Authors: Christopher C F Howe; Nicola Swann; Owen Spendiff; Anna Kosciuk; Elizabeth K L Pummell; Hannah J Moir Journal: Eur J Appl Physiol Date: 2021-03-11 Impact factor: 3.078