Developing a Variation Index for Understanding Step Characteristics in the Long Jump Approach Run
DOI:
https://doi.org/10.17309/tmfv.2025.1.17Keywords:
biomechanics, principal component analysis, PLS-SEM method, motion analysis, latent variableAbstract
Objectives. The prime objective of the study was to develop a new variation index that can be used to identify the mechanical variations in the step pattern of the approach run.
Materials and methods. Twelve national-level long jumpers (age 19 ± 0.32 years) were analyzed in this study. Five high-speed action cameras with a resolution of 1920 x 1080 pixels at 120 frames per second were used. The data obtained were digitized with Quintic Motion Analysis software (v.33). In order to construct a Variation Index, the method of partial least squares structural equation modeling (PLS-SEM) was used. Additionally, a Principal Component Analysis (PCA) was applied to construct latent variable for the PLS-SEM.
Results. The results of the study revealed that step variation was started at the last 5th step of the approach run. Moreover, mechanical variation was observed among the last three steps of the approach run. These findings suggest that mechanical preparation for the final take-off in the long jump might start during the middle phase of the approach run.
Conclusions. The Variation Index introduced in this study offers a detailed understanding of an individual’s approach run technique. Coaches and athletes can use this information to implement precise training strategies for optimizing the preparation for the final take-off during the approach run.
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