Annals of Biomedical Engineering

, Volume 45, Issue 12, pp 2762–2774 | Cite as

Why are Antagonist Muscles Co-activated in My Simulation? A Musculoskeletal Model for Analysing Human Locomotor Tasks

  • Adrian K. M. LaiEmail author
  • Allison S. Arnold
  • James M. Wakeling


Existing “off-the-shelf” musculoskeletal models are problematic when simulating movements that involve substantial hip and knee flexion, such as the upstroke of pedalling, because they tend to generate excessive passive fibre force. The goal of this study was to develop a refined musculoskeletal model capable of simulating pedalling and fast running, in addition to walking, which predicts the activation patterns of muscles better than existing models. Specifically, we tested whether the anomalous co-activation of antagonist muscles, commonly observed in simulations, could be resolved if the passive forces generated by the underlying model were diminished. We refined the OpenSim™ model published by Rajagopal et al. (IEEE Trans Biomed Eng 63:1–1, 2016) by increasing the model’s range of knee flexion, updating the paths of the knee muscles, and modifying the force-generating properties of eleven muscles. Simulations of pedalling, running and walking based on this model reproduced measured EMG activity better than simulations based on the existing model—even when both models tracked the same subject-specific kinematics. Improvements in the predicted activations were associated with decreases in the net passive moments; for example, the net passive knee moment during the upstroke of pedalling decreased from 36.9 N m (existing model) to 6.3 N m (refined model), resulting in a dramatic decrease in the co-activation of knee flexors. The refined model is available from and is suitable for analysing movements with up to 120° of hip flexion and 140° of knee flexion.


Musculoskeletal model Hill-type muscle model Simulation Passive force Running Pedalling 



We thank Taylor Dick, Sidney Morrison and Glen Lichtwark for their assistance in collecting and post-processing the experimental data used in this study, and we are grateful to Andy Biewener and Carolyn Eng for helpful discussions. Funding for this work was provided by the National Institutes of Health Grant 2R01AR055648.

Supplementary material

10439_2017_1920_MOESM1_ESM.pdf (113 kb)
Supplementary material 1 (PDF 113 kb)
10439_2017_1920_MOESM2_ESM.pdf (90 kb)
Supplementary material 2 (PDF 89 kb)


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Copyright information

© Biomedical Engineering Society 2017

Authors and Affiliations

  • Adrian K. M. Lai
    • 1
    Email author
  • Allison S. Arnold
    • 2
  • James M. Wakeling
    • 1
  1. 1.Department of Biomedical Physiology and KinesiologySimon Fraser UniversityBurnabyCanada
  2. 2.Department of Organismic and Evolutionary Biology, Concord Field StationHarvard UniversityBedfordUSA

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