Neuromusculoskeletal Modeling for Neurorehabilitation Technologies

Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 1)

Abstract

We present a methodology based on computational neuromusculoskeletal models of the human body as a means of predicting the actions of muscles during dynamic motor tasks. In this scenario, experimental surface electromyograms (EMG) are used to “drive” the simulated muscles in the model. This also allows estimat ing muscle activation patterns for muscles from which EMGs cannot be measured and allows adjusting experimental EMG recording that may be subject to measurement errors. Furthermore, we present another methodology that uses a lowdimensional set of basic muscle activation primitives (APs) to model the resulting motor programs that coordinate the recruitment of muscles during human locomotion. The APs are then used to perform musculoskeletal simulation of locomotion tasks. We describe the theoretical aspects of the proposed methodology and discuss its implications in neurorehabilitation technologies. Furthermore, we present experimental results that demonstrate the benefits of the new method.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lloyd, D.G., Besier, T.F.: An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J. of Biomech. 36, 765–776 (2003)CrossRefGoogle Scholar
  2. 2.
    Sartori, M., Reggiani, M., van den Bogert, A.J., Lloyd, D.G.: Estimation of musculotendon kinematics in lage musculoskeletal models using multidimensional B-Splines. Journal of Biomechanics 45, 595–601 (2012)CrossRefGoogle Scholar
  3. 3.
    Sartori, M., Reggiani, M., Pagello, E., Lloyd, D.G.: Modelling the Human Knee for Assistive Technologies. IEEE Transactions on Biomedical Engineering (in press)Google Scholar
  4. 4.
    Ivanenko, Y.P., Poppele, R.E., Lacquaniti, F.: Five basic muscle activation patterns account for muscle activity during human locomotion. J. Physiol. 556, 267–282 (2004)CrossRefGoogle Scholar
  5. 5.
    Anderson, F.C., Pandy, M.G.: Static and dynamic optimization solutions for gait are practically equivalent. Journal of Biomechanics 34, 153–161 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Medical University GöttingenGottingenGermany

Personalised recommendations