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Muscle coordination retraining inspired by musculoskeletal simulations: a study on reducing knee loading

Scott D Uhlrich, Rachel W Jackson, Ajay Seth, Julie A Kolesar, Scott L Delp
doi: https://doi.org/10.1101/2020.12.30.424841
Scott D Uhlrich
1Departments of Mechanical Engineering, Stanford University, Stanford, CA 94305
2Departments of Bioengineering, Stanford University, Stanford, CA 94305
3Musculoskeletal Research Laboratory, VA Palo Alto Healthcare System, Palo Alto, CA 94304
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  • For correspondence: suhlrich@stanford.edu
Rachel W Jackson
2Departments of Bioengineering, Stanford University, Stanford, CA 94305
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Ajay Seth
5Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands 2628 CD
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Julie A Kolesar
2Departments of Bioengineering, Stanford University, Stanford, CA 94305
3Musculoskeletal Research Laboratory, VA Palo Alto Healthcare System, Palo Alto, CA 94304
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Scott L Delp
1Departments of Mechanical Engineering, Stanford University, Stanford, CA 94305
2Departments of Bioengineering, Stanford University, Stanford, CA 94305
4Departments of Orthopaedic Surgery, Stanford University, Stanford, CA 94305
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Abstract

Humans typically coordinate their muscles to meet movement objectives like minimizing energy expenditure. In the presence of pathology, new objectives gain importance, like reducing loading in an osteoarthritic joint, but people often do not change their muscle coordination patterns to meet these new objectives. Here we use musculoskeletal simulations to identify simple changes in coordination that can be taught by providing feedback of electromyographic activity to achieve a therapeutic goal—reducing joint loading. Our simulations predicted that changing the relative activation of the redundant ankle plantarflexors could reduce knee contact force during walking, but it was unclear whether humans could re-coordinate redundant muscles during a complex task like walking. With simple biofeedback of electromyographic activity, healthy individuals reduced the ratio of gastrocnemius to soleus muscle activation by 25±15% (p=0.004). The resulting “gastrocnemius avoidance” gait pattern reduced the late-stance peak of simulation-estimated knee contact force by 12±12% (p=0.029). Simulation-informed muscle coordination retraining could be a promising treatment for knee osteoarthritis and a powerful tool for optimizing coordination for a variety of rehabilitation and performance applications.

Competing Interest Statement

Stanford University has applied for a patent on behalf of SDU and SLD describing the muscle coordination retraining technique, entitled "Real-time electromyography feedback to change muscle activity during complex movements." The patent is pending at the time of manuscript submission. The authors have no other competing interests to disclose.

Footnotes

  • https://simtk.org/projects/coordretraining

  • https://simtk.org/projects/fbmodpassivecal

  • https://github.com/stanfordnmbl/MatlabStaticOptimization

  • https://github.com/stanfordnmbl/PassiveMuscleForceCalibration

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted January 01, 2021.
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Muscle coordination retraining inspired by musculoskeletal simulations: a study on reducing knee loading
Scott D Uhlrich, Rachel W Jackson, Ajay Seth, Julie A Kolesar, Scott L Delp
bioRxiv 2020.12.30.424841; doi: https://doi.org/10.1101/2020.12.30.424841
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Muscle coordination retraining inspired by musculoskeletal simulations: a study on reducing knee loading
Scott D Uhlrich, Rachel W Jackson, Ajay Seth, Julie A Kolesar, Scott L Delp
bioRxiv 2020.12.30.424841; doi: https://doi.org/10.1101/2020.12.30.424841

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