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Neuromusculoskeletal Modeling Pipeline

What is being modeled?
The human neuromusculoskeketal system.
Description & purpose of resource

Model-based personalized treatment design for neurologic and orthopedic movement impairments. The software is developed entirely in Matlab and adds Model Personalization and Treatment Optimization capabilities to OpenSim.

Spatial scales
tissue
organ
whole organism
Temporal scales
10-3 - 1 s
1 - 103 s
This resource is currently
mature and useful in ongoing research
likely to be usable without detailed knowledge of its internals
Has this resource been validated?
Yes
How has the resource been validated?

The underlying computational technologies for each of the four tools in the Model Personalization Toolset and each of the three tools in the Treatment Optimization Toolset have been validated in peer-reviewed journal publications.

Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
Yes
Which resources?

OpenSim musculoskeletal modeling software

Key publications (e.g. describing or using resource)
  1. Ao, D.*, Vega, M.M.*, Shourijeh, M.S.*, Patten, C., and Fregly, B.J. (2022) EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation. Frontiers in Bioengineering and Biotechnology 10, Article 962959.
  2. Li, G.*, Ao, D.*, Vega, M.M.*, Shourijeh, M.S.*, Zandiyeh, P., Chang, S.-H., Lewis, V.O., Dunbar, N.J.*, Babazadeh-Naseri, A.*, Baines, A.J.*, and Fregly, B.J. (2022) A computational method for estimating trunk muscle activations during gait using lower extremity muscle synergies. Frontiers in Bioengineerinig and Biotechnology 10, Article 964359
  3. Vega, M.M.*, Li, G.*, Shourijeh, M.S.*, Ao, D.*, Weinschenk, R.C.*, Patten, C., Font-Llagunes, J.M., Lewis, V.O., and Fregly, B.J. (2022) Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction. Frontiers in Bioengineering and Biotechnology 10, Article 855870.
  4. Fregly, B.J. (2021) A conceptual blueprint for making neuromusculoskeletal models clinically useful. Applied Sciences, Special Issue on Musculoskeletal Models in a Clinical Perspective 11, Article 2037.
  5. Ao, D.*, Shourijeh, M.S.*, Patten, C., and Fregly, B.J. (2020) Evaluation of synergy extrapolation for predicting unmeasured muscle excitations from measured muscle synergies. Frontiers in Computational Neuroscience 14, Article 108.
  6. Arones, M.M.*, Shourijeh, M.S.*, Patten, C., and Fregly, B.J. (2020) Musculoskeletal model personalization affects metabolic cost estimates for walking. Frontiers in Bioengineering and Biotechnology 8, Article 1358.
  7. Shourijeh, M.*† and Fregly, B.J. (2020) Muscle synergies modify static optimization estimates of joint stiffness during walking. Journal of Biomechanical Engineering 142, 011011 (9 pages).
  8. Sauder, N.R.*, Allen, J.L., Ting, L.H., Kesar, T.M., and Fregly, B.J.† (2019) Computational design of FastFES treatment to improve propulsive force symmetry during post-stroke gait: A feasibility study. Frontiers in Neurorobotics 13, 80.
  9. Bianco, N.A.*, Patten, C., and Fregly, B.J.† (2018) Can measured synergy excitations accurately construct unmeasured muscle excitations? Journal of Biomechanical Engineering 140, 011011 (10 pages).
  10. Eskinazi, I.* and Fregly, B.J.† (2018) A computational framework for simultaneous estimation of muscle and joint contact forces and body motion using optimization and surrogate modeling. Medical Engineering & Physics 54, 56-64.
  11. Meyer, A.J.*, Patten, C., and Fregly, B.J. (2017) Lower extremity EMG-driven modeling of walking with automated adjustment of musculoskeletal geometry. PLoS One 12, e0179698.
  12. De Groote, F.*†, Kinney, A.L.*, Rao, A.V., and Fregly, B.J. (2016) Evaluation of direct collocation optimal control problem formulations for solving the muscle redundancy problem. Annals of Biomedical Engineering 44, 2922-2236.
  13. Eskinazi, I.* and Fregly, B.J. (2016) An open-source toolbox for surrogate modeling of joint contact mechanics. IEEE Transactions on Biomedical Engineering 63, 269-277.
  14. Jackson, J.N.*, Hass, C.J., and Fregly, B.J. (2016) Development of a subject-specific foot-ground contact model for gait. Journal of Biomechanical Engineering 138, 091002 (12 pages).
  15. Meyer, A.J.*, Eskinazi, I.*, Jackson, J.N.*, Rao, A.V., Patten, C., and Fregly, B.J. (2016) Muscle synergies facilitate computational prediction of subject-specific walking motions. Frontiers in Bioengineering and Biotechnology 4, Article 77.
  16. Eskinazi, I.* and Fregly, B.J. (2015) Surrogate modeling of deformable joint contact using artificial neural networks. Medical Engineering & Physics 37, 885-891.
  17. Walter J.P.*, Kinney, A.L.*, Banks, S.A., D’Lima, D.D., Besier, T.F., Lloyd, D.G., and Fregly, B.J. (2014) Muscle synergies may improve optimization prediction of knee contact forces during walking. Journal of Biomechanical Engineering 136, 021031 (9 pages).

 

PI contact information
B.J. Fregly
Keywords
neuromusculoskeletal modeling, simulation, and optimization
personalized neuromusucloskeletal models
computational treatment design
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Model type
statistical
dynamical
geometrical
Data type
electrical
systemic