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Predictive Models in Biomechanics

  • John RasmussenEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 831)

Abstract

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.

Keywords

Musculoskeletal models Running Statistics Principal component analysis 

Notes

Acknowledgements

This work was supported by Innovation Fund Denmark.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Aalborg UniversityAalborgDenmark

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