Principal Components for Practice-Oriented Measurement of Running Technique: A Proof-Of-Concept Study

Abstract

This study aims to construct valid and practically applicable running technique measures using principal component analysis (PCA). We hypothesized that data-driven principal movements (PMs), derived from deliberately instructed opposite technique variations, would significantly distinguish these variations and could serve as quantitative measures of running technique as described by practitioners. 20 experienced runners were instructed to vary 14 distinct running technique elements into two opposing directions (e.g., forward and backward lean for a technique element representing horizontal movements). Elements and their variations were selected based on visual descriptions from practitioners found in running literature. Kinematic data were collected on a treadmill using optical motion capture and analyzed using a PCA-based approach to determine running-specific technique measures per technique element. By combining trials with opposing technique variations, variance in the data was purposefully produced, which in turn caused the resultant principal movements to align with the intended technique element. For all of the 14 technique elements, a valid measure—in the sense that the inputted opposite variations were significantly distinguishable within this measure—could be constructed. The measures could further be applied to the habitual running technique of the group of tested runners. The results of this study demonstrate the construct validity and applicability of the presented approach to measure running technique. This method can provide runners and coaches with valuable feedback and will enable future studies to investigate running technique, quantified through practice-informed measures, in the context of performance, injury risk, or adaptations to equipment.