Computer simulation based parameter selection for resistance exercise

Oggie Arandelovic*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In contrast to most scientific disciplines, sports science research has been characterized by comparatively little effort investment in the development of relevant phenomenologi-cal models. Scarcer yet is the application of said models in practice. We present a framework which allows resistance training practitioners to employ a recently proposed neu-romuscular model in actual training program design. The first novelty concerns the monitoring aspect of coaching. A method for extracting training performance characteristics from loosely constrained video sequences, effortlessly and with minimal human input, using computer vision is described. The extracted data is subsequently used to fit the underlying neuromuscular model. This is achieved by solving an inverse dynamics problem corresponding to a particular exercise. Lastly, a computer simulation of hypothetical training bouts, using athlete-specific capability parameters, is used to predict the effected adaptation and changes in performance. The software described here allows the practitioner to manipulate hypothetical training parameters and immediately see their effect on predicted adaptation for a specific athlete. Thus, this work presents a holistic view of the monitoring-assessment-adjustment loop.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Modelling and Simulation
Number of pages10
Publication statusPublished - 2013
Event24th IASTED International Conference on Modelling and Simulation, MS 2013 - Banff, AB, Canada
Duration: 17 Jul 201319 Jul 2013


Conference24th IASTED International Conference on Modelling and Simulation, MS 2013
CityBanff, AB


  • Muscle
  • Powerlifting
  • Strength
  • Training
  • Weight


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