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.
This work was supported by the ERC Advanced Grant DEMOVE.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
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)
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)
Sartori, M., Reggiani, M., Pagello, E., Lloyd, D.G.: Modelling the Human Knee for Assistive Technologies. IEEE Transactions on Biomedical Engineering (in press)
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)
Anderson, F.C., Pandy, M.G.: Static and dynamic optimization solutions for gait are practically equivalent. Journal of Biomechanics 34, 153–161 (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sartori, M., Farina, D. (2013). Neuromusculoskeletal Modeling for Neurorehabilitation Technologies. In: Pons, J., Torricelli, D., Pajaro, M. (eds) Converging Clinical and Engineering Research on Neurorehabilitation. Biosystems & Biorobotics, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34546-3_201
Download citation
DOI: https://doi.org/10.1007/978-3-642-34546-3_201
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34545-6
Online ISBN: 978-3-642-34546-3
eBook Packages: EngineeringEngineering (R0)