A review of forward-dynamics simulation models for predicting optimal technique in maximal effort sporting movements

McErlain-Naylor, S.A., King, M.A. and Felton, P.J. ORCID: 0000-0001-9211-0319, 2021. A review of forward-dynamics simulation models for predicting optimal technique in maximal effort sporting movements. Applied Sciences, 11 (4): 1450. ISSN 2076-3417

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The identification of optimum technique for maximal effort sporting tasks is one of the greatest challenges within sports biomechanics. A theoretical approach using forward-dynamics simulation allows individual parameters to be systematically perturbed independently of potentially confounding variables. Each study typically follows a four-stage process of model construction, parameter determination, model evaluation, and model optimization. This review critically evaluates forward-dynamics simulation models of maximal effort sporting movements using a dynamical systems theory framework. Organismic, environmental, and task constraints applied within such models are critically evaluated, and recommendations are made regarding future directions and best practices. The incorporation of self-organizational processes representing movement variability and "intrinsic dynamics" remains limited. In the future, forward-dynamics simulation models predicting individual-specific optimal techniques of sporting movements may be used as indicative rather than prescriptive tools within a coaching framework to aid applied practice and understanding, although researchers and practitioners should continue to consider concerns resulting from dynamical systems theory regarding the complexity of models and particularly regarding self-organization processes.

Item Type: Journal article
Publication Title: Applied Sciences
Creators: McErlain-Naylor, S.A., King, M.A. and Felton, P.J.
Publisher: MDPI
Date: 5 February 2021
Volume: 11
Number: 4
ISSN: 2076-3417
Rights: Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 09 Feb 2021 09:52
Last Modified: 31 May 2021 15:07
URI: https://irep.ntu.ac.uk/id/eprint/42236

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