Muscle-driven simulations of human and animal motion are widely used to complement physical experiments for studying movement dynamics. Musculotendon models are an essential component of muscle-driven simulations, yet neither the computational speed nor the biological accuracy of the simulated forces has been adequately evaluated. Here we compare the speed and accuracy of three musculotendon models: two with an elastic tendon (an equilibrium model and a damped equilibrium model) and one with a rigid tendon. Our simulation benchmarks demonstrate that the equilibrium and damped equilibrium models produce similar force profiles but have different computational speeds. At low activation, the damped equilibrium model is 29 times faster than the equilibrium model when using an explicit integrator and 3 times faster when using an implicit integrator; at high activation, the two models have similar simulation speeds. In the special case of simulating a muscle with a short tendon, the rigid-tendon model produces forces that match those generated by the elastic-tendon models, but simulates 2–54 times faster when an explicit integrator is used and 6–31 times faster when an implicit integrator is used. The equilibrium, damped equilibrium, and rigid-tendon models reproduce forces generated by maximally-activated biological muscle with mean absolute errors less than 8.9%, 8.9%, and 20.9% of the maximum isometric muscle force, respectively. When compared to forces generated by submaximally-activated biological muscle, the forces produced by the equilibrium, damped equilibrium, and rigid-tendon models have mean absolute errors less than 16.2%, 16.4%, and 18.5%, respectively. To encourage further development of musculotendon models, we provide implementations of each of these models in OpenSim version 3.1 and benchmark data online, enabling others to reproduce our results and test their models of musculotendon dynamics.
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February 2013
Research-Article
Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics
Matthew Millard,
Thomas Uchida,
Scott L. Delp
Scott L. Delp
1
Department of Bioengineering,
Department of Mechanical Engineering,
Stanford, CA 94305
e-mail: delp@stanford.edu
Department of Mechanical Engineering,
Stanford University
,Stanford, CA 94305
e-mail: delp@stanford.edu
1Corresponding author.
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Matthew Millard
e-mail: mjhmilla@stanford.edu
Thomas Uchida
e-mail: tkuchida@stanford.edu
Ajay Seth
Scott L. Delp
Department of Bioengineering,
Department of Mechanical Engineering,
Stanford, CA 94305
e-mail: delp@stanford.edu
Department of Mechanical Engineering,
Stanford University
,Stanford, CA 94305
e-mail: delp@stanford.edu
1Corresponding author.
Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received November 16, 2012; final manuscript received January 7, 2013; accepted manuscript posted January 18, 2013; published online February 7, 2013. Editor: Victor H. Barocas.
J Biomech Eng. Feb 2013, 135(2): 021005 (11 pages)
Published Online: February 7, 2013
Article history
Received:
November 16, 2012
Revision Received:
January 7, 2013
Accepted:
January 18, 2013
Citation
Millard, M., Uchida, T., Seth, A., and Delp, S. L. (February 7, 2013). "Flexing Computational Muscle: Modeling and Simulation of Musculotendon Dynamics." ASME. J Biomech Eng. February 2013; 135(2): 021005. https://doi.org/10.1115/1.4023390
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