Predictive Models in Biomechanics
This paper investigates the opportunity of predictive musculoskeletal models that do not require experimental input of kinematics and ground reaction forces. First, the requirements of such models are reviewed and, subsequently, an example model of running is derived by means of principal component analysis. The generation of different running styles using the model is demonstrated, and we conclude that this type of models has the potential to predict motion behavior given shallow input describing the individual.
KeywordsMusculoskeletal models Running Statistics Principal component analysis
This work was supported by Innovation Fund Denmark.
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