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In contrast to most scientific disciplines, sports science research has beencharacterized by comparatively little effort investment in the development ofrelevant phenomenological models. Scarcer yet is the application of said modelsin practice. We present a framework which allows resistance trainingpractitioners to employ a recently proposed neuromuscular model in actualtraining program design. The first novelty concerns the monitoring aspect ofcoaching. A method for extracting training performance characteristics fromloosely constrained video sequences, effortlessly and with minimal human input,using computer vision is described. The extracted data is subsequently used tofit the underlying neuromuscular model. This is achieved by solving an inversedynamics problem corresponding to a particular exercise. Lastly, a computersimulation of hypothetical training bouts, using athlete-specific capabilityparameters, is used to predict the effected adaptation and changes inperformance. The software described here allows the practitioner to manipulatehypothetical training parameters and immediately see their effect on predictedadaptation for a specific athlete. Thus, this work presents a holistic view ofthe monitoring-assessment-adjustment loop.

Computer simulation based parameter selection for resistance exercise