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

Abstract

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.

Prediction of Propulsion Kinematics and Performance in Wheelchair Rugby

“…While an important adaption to include for these athletes, the added features of the new model should be considered a minor addition to the original model. The results show that whilst this linkage model approach might be appropriate for some cases, it is unlikely to be suitable for all athletes; some are likely to require more detailed models that greater reflect their activity limitation (McErlain-Naylor et al, 2021 ). This may be the case for athletes with greater activity limitation (lower classification scores), who are less able to adapt technique to wheelchair set-up.…”

“…However, musculoskeletal models currently find it difficult to independently scale individual body segments which would limit their applicability to amputees. The selection of modeling approach should therefore consider the ability to accurately measure and replicate individual capabilities (Lewis, 2018 ; McErlain-Naylor et al, 2021 ) as well as time restraints around any prescription approach.…”

“…This is clearly a crucial area for improving the well-being of wheelchair users, but it is unable to address performance aspects such as sprint or agility times. Due to the complexity of musculoskeletal models, creating valid individual representations of anthropometrics and muscular function is also an extensive process (Dembia et al, 2020 ; McErlain-Naylor et al, 2021 ). To address this, a linkage model has previously been developed that is able to predict changes in propulsion kinematics (contact and release positions) for changing seat height [the vertical distance from the rear of the seat to main (rear) wheel axle] and seat depth (often referred to as fore-aft position, the horizontal distance from rear of the seat to main (rear) wheel axle) during daily propulsion (Richter, 2001 ; Leary et al, 2012 ).…”

A Simulation of the Effects of Badminton Serve Release Height

“…If successful, such an approach would determine the best serve for each of the two conditions, and they could subsequently be compared. Realistic optimization, however, would require the consideration of sensitivity to noise in the neuromuscular system, as discussed by McErlain-Naylor et al [13], and the difficulty of learning a new movement pattern in order to cope with the new serve height. The strategy of the elite player in the present study, when serving from the uncustomary lower height, was to flex her knees to retain the familiar movement pattern in her upper body.…”

Physics-informed Deep Learning for Musculoskeletal Modelling: Predicting Muscle Forces and Joint Kinematics from Surface EMG

“…H UMAN movements encompass complex interactions of the neuromuscular system [1]. As a powerful omputational simulation tool, musculoskeletal model can be applied for detailed biomechanical analysis to understand these interactions, which would be beneficial to various applications ranging from evaluating rehabilitation treatment [2], enhancing performance of athlete [3], [4], optimising robotic design for impaired individuals [5], to surgical planning and intervention [6].…”