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

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posted on 2021-05-20, 09:17 authored by Stuart A McErlain-Naylor, Mark KingMark King, Paul J Felton
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.

History

School

  • Sport, Exercise and Health Sciences

Published in

Applied Sciences

Volume

11

Issue

4

Publisher

MDPI AG

Version

  • VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

2021-02-02

Publication date

2021-02-05

Copyright date

2021

eISSN

2076-3417

Language

  • en

Depositor

Prof Mark King. Deposit date: 20 May 2021

Article number

1450