ArticleHeliyon2023
Stride-to-stride variability and fluctuations at intensities around lactate threshold in distance runners.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Quantitative assessment of gait alterations and variability in sulky-driven Standardbred trotters after a standardised exercise test.Equine veterinary journal · 2026Article
- The Effect of Non-Invasive Brain Stimulation on Running Performance and Inertial Measurement Unit-Derived Spatiotemporal Parameters in Endurance-Trained Runners.Sensors (Basel, Switzerland) · 2026Article
- Bioinformatics-Inspired IMU Stride Sequence Modeling for Fatigue Detection Using Spectral-Entropy Features and Hybrid AI in Performance Sports.Sensors (Basel, Switzerland) · 2026Article
- Acute whole-body vibration as a recovery strategy did not alter the content of gluteus medius monocarboxylate-transporters, lactatemia, and acidosis induced by intense exercise in horses.Frontiers in veterinary science · 2025Article
- Improved running gait parameter estimation from single foot-mounted IMU data based on refined event detection.Frontiers in bioengineering and biotechnology · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
Stride-to-stride variability and fluctuations in running have been widely investigated in relation to fatigue, injury, and other factors. However, no studies have examined the relationship of stride-to-stride variability and fluctuations with lactate threshold (LT), a well-known performance indicator for distance runners that represents the threshold at which fast-twitch muscle fibers are activated and the glycolytic system is hyperactivated. In this study, we examined a relationship between LT and stride-to-stride variability and fluctuations in trained middle- and long-distance runners (n = 33). All runners were asked to perform multistage graded exercise tests while wearing accelerometers on the upper surface of their shoes. The LT was determined by measuring blood lactate concentrations after each stage. Three gait parameters for each step were calculated based on the acceleration data: stride time (ST), ground contact time (CT), and peak acceleration (PA). The coefficient of variation (CV) and the long-range correlations (α) for each parameter were also calculated. The effects of the runner's group and the relative intensity for CV and α on gait parameters were evaluated using a two-way repeated measures analysis of variance. Although no significant effect was observed in the CV and α of ST, significant intensity main effects were observed for the CV and α of CT and PA. The lack of significant changes in ST might be the result of runners' adequate control of ST to minimize energy cost. All the parameters showing significant changes with increasing intensity decreased dramatically when they were close to LT. This might have been caused by an increase in physiological load near LT and be interpreted as a variation in motor control because of alternations in the mobilized muscle fibers and physiological changes around the LT. The α should be useful for non-invasive LT detection.
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