A Review of Forward-Dynamics Simulation Models for Predicting Optimal Technique in Maximal Effort Sporting Movements

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 variab...

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Bibliographic Details
Published in:Applied sciences 2021-02, Vol.11 (4), p.1450
Main Authors: McErlain-Naylor, Stuart A., King, Mark A., Felton, Paul J.
Format: Article
Language:English
Subjects:
Best practice
Biomechanics
Computer simulation
Constraint modelling
constraints
Dynamic systems theory
Dynamical systems
dynamical systems theory
evaluation
Human mechanics
Investigations
Mathematical functions
Optimization
parameters
Process parameters
Simulation
System theory
torque-driven
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Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11041450