The Impact of Training Load on Running Gait Variability: A Pilot Study

Authors

  • Johnny Padulo Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
  • Giacomo Manenti Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
  • Fabio Esposito Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy

Keywords:

human locomotion; footstep pattern coordination; running performance; endurance runners

Abstract

Purpose: Running gait variability appears to be a new metric related to fatigue in long-distance runners. However, no study
has verified the changes in gait variability over a longitudinal study involving well-experienced runners. Therefore, the
aim of this study was to investigate the changes in gait variability in distance runner before and after a 9-week endurance
training program.
Methods: A male runner (age 23 years; body mass 58 kg; stature 1.70 m, BMI 20 kg·m−2) completed two critical speed (CS)
test and six trial at different speeds (calculated by CS) with 9-week of training in-between. At the same time heart rate
(HR) was continuously recorded and normalized as a percentage of the maximal heart rate (220 - age) %HRmax, serving as
a proxy for metabolic expenditure. Additionally, kinematic (contact time (CT), flight time (FT), step length (SL), step rate
(SR)) and kinetic measurements (leg (kvert) and vertical (kleg) stiffness), were recorded. While the running gait variability was
calculated as phase coordination index (PCI).
Results: CS and HR were 16.40/18.00 km·h-1 and 93.19±1.23/93.81±2.38 %HRmax in baseline and after the training,
respectively. The kinematic and kinetic variables studied at different speeds (13.80-14.40-15.00-15.70-16.40-17.10 km·h-1)
showed a significative training effect vs baseline conditions for CT (P= .010), FT (P= .010), SL (P= .002), SR (P= .002), kvert (P=
.003), kleg (P= .0001). At the same way the metabolic demand and PCI changed significantly after the training compared to the
baseline condition for average/maximum HR (P= .009 – 0.024, respectively) and PCI (P= .009).
Conclusions: These results suggest that gait variability is one mechanical determinant that demonstrates the adaptation of
training load when neuromuscular output related to physiological efforts is under stress conditions, such as running training.
Therefore, PCI could be a useful tool for monitoring the impact of running training load on bilateral running coordination.

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Published

31-12-2023 — Updated on 06-01-2024

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How to Cite

Padulo, J., Manenti, G., & Esposito, F. (2024). The Impact of Training Load on Running Gait Variability: A Pilot Study. Acta Kinesiologica, 17(2), 29–34. Retrieved from https://akinesiologica.com/ojs_3.3.0-7/index.php/akinesiologica/article/view/127 (Original work published December 31, 2023)

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Section

Original Scientific Article