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Fatigue related changes in rearfoot eversion: a means of functionally grouping runners?

Ben Langley
Published in: European journal of sport science (2022)
Fatigue alters rearfoot kinematics on an individual basis and may offer a means of functionally grouping runners. This proof of concept study aimed to determine whether fatigue related changes in rearfoot eversion could be used to functionally group runners. Sixteen male recreational runners had their frontal plane rearfoot kinematics recorded by a three-dimensional motion capture system before and after a 5km run. The magnitude of change in frontal plane rearfoot kinematics pre- to post-fatigue was calculated and K-means clustering used to identify functional groups based upon these changes. T -tests with statistical parametric mapping were used to compare fatigue related changes both within and between clusters. Two clusters or functional groups were evident within the data set. Nine participants were allocated to cluster 1 and displayed small and insignificant changes in frontal plane rearfoot motion post-fatigue. In contrast, the remaining seven participants were assigned to cluster 2 and displayed significant increases in rearfoot eversion between 3 and 84% of the stance phase post-fatigue. These findings prove the concept that fatigue related changes in rearfoot eversion can be used to functionally group participants. Additionally, the differing fatigue related changes reported by each group may alter the injury risk, training and footwear needs of each group. HighlightsFatigue related changes in frontal plane rearfoot motion can be used to functionally group individuals.Cluster 1 display small and insignificant fatigue related changes, which suggests they can maintain their habitual movement pathway.Cluster 2 displayed significant increases in rearfoot eversion for the majority of the stance phase, suggesting an inability to maintain their habitual movement pathway, which may increase injury risk.
Keyphrases
  • sleep quality
  • depressive symptoms
  • functional connectivity
  • rna seq
  • big data
  • artificial intelligence