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Predictive Models in Biomechanics

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Biomechanics in Medicine and Biology (BIOMECHANICS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 831))

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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.

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Acknowledgements

This work was supported by Innovation Fund Denmark.

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Authors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    John Rasmussen

Authors
  1. John Rasmussen
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Corresponding author

Correspondence to John Rasmussen .

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Editors and Affiliations

  1. Division of Biomedical Engineering, Department of Mechanical Engineering, University of Zielona Góra, Zielona Góra, Poland

    Katarzyna Arkusz

  2. Division of Biomedical Engineering, Department of Mechanical Engineering, University of Zielona Góra, Zielona Góra, Poland

    Romuald Będziński

  3. Division of Biomedical Engineering, Department of Mechanical Engineering, University of Zielona Góra, Zielona Góra, Poland

    Tomasz Klekiel

  4. Division of Biocybernetics and Biomedical Engineering, Department of Mechanical Engineering, Bialystok University of Technology, Białystok, Poland

    Szczepan Piszczatowski

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Rasmussen, J. (2019). Predictive Models in Biomechanics. In: Arkusz, K., Będziński, R., Klekiel, T., Piszczatowski, S. (eds) Biomechanics in Medicine and Biology. BIOMECHANICS 2018. Advances in Intelligent Systems and Computing, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-97286-2_9

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