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Predictive Simulation of Rowing Exercise

An exercise machine presents a specific geometrical and mechanical environment to the user. These design parameters affect how the exercise is performed and which forces are generated in musculoskeletal tissues. If we are able to predict these effects during the design process, exercise outcomes can be improved. Current approaches aim at presenting simple conditions such as constant load or constant speed, or replicate existing sports-related exercise conditions such as rowing, weightlifting and bicycling. There is, however, much more design freedom which remained unexplored. To predict human execution and optimize machine parameters, the human musculoskeletal dynamics and adaptive neuromuscular control should be taken to account. Here we will use a computational method based on musculoskeletal modeling and optimal control to predict how mechanical parameters alter human performance in rowing exercise. The specific purpose of this research is to investigate the effects of resistance parameters on movements and forces generated by the arm during periodic arm flexion exercise.