Versions Compared


  • This line was added.
  • This line was removed.
  • Formatting was changed.

Team Members

  • Nick Bianco
  • Rachel Troutman


Project Summary

Widget Connector

GitHub Repository



    Set up GitHub repository (organization of data files, source code, etc) [Nick]


    Download and configure GPOPS-II, DeGroote muscle redundancy solver [Rachel]


    Choose and modify OpenSim model [Nick, Rachel]


    Review relevant optimal control theory and numerical methods (i.e. direct collocation) [Nick, Rachel]


    Problem #1 - Reproduce Quinlivan 2017 study with Gait2354 default data


      Digitize assistive curves from paper [Rachel]


      Create generic exosuit assistive torque subroutine [Nick]

    •  Run preliminary simulation [Rachel, Nick]
  •  Problem #2 - Reproduce Quinlivan 2017 with shifted hip assistive torque to align with biological peak [Rachel]

    Problem #3 - Examine tradeoff in hip flexion and ankle plantarflexion moment arms [Nick]


    Problem #4 - Examine tradeoff in hip extension and hip abduction moment arms [Nick]


    Problem #5 - Examine tradeoff in third case (need to define) [Rachel (probably)]

  •  [Optional] Compare estimations using metabolic cost solutions [Nick]
  •  [Optional] Compare estimations using device mass cost solutions [Rachel] 

    Organize results and produce figures


      Find a way to condense current results


    Draft final presentation


    Draft demo video

  •  Draft final report


The Our general optimization problem was set up as shown below. approach was solving a muscle redundancy problem using the Gait2354 OpenSim default model and associated data. The problem formulation is based on the direct collocation optimal control framework for solving the muscle redundancy published by Friedl De Groote. 

Image Added

A cost function was minimized subject to a set of constraints including tracking the joint moments calculated from inverse dynamics. The joint moments are made up of contributions from the muscles, reserve actuators, and assistive moments from the exosuit.

Image Removed

Depending on the problem being solved, the assistive torques of the device were either prescribed or solved for as part of the optimization.


In this first problem, the goal was to simulate the experiments done with the soft exosuit in a paper by Quinlivan et al. We wanted to see if we could recreate their metabolic cost savings and predict what would happen above the maximum condition they tested. The cost function for this problem was a sum of excitations and activations of the muscles used to create the desired walking motion. For the first four conditions (blue curves), the exosuit moments were pulled directly from the paper. The next six conditions are scaled versions of these curves. The applied moments are shown below as a function of time of the stance phase. The associated change in metabolic rate for each condition is shown on the right. The simulation results are shown as colored dots and the experimental results from the paper are shown as bars. 


The same general trend of decreasing metabolic cost as peak assistive force increases is seen in both the simulation and experimental results. The simulations results however, underestimate the metabolic savings at the higher force levels. All metabolic costs were calculated using the Umberger metabolics model. The simulations suggest that there is some opportunity to further decrease metabolic cost with with device by increasing the assistive force above the maximum experimental trial, but the linear trend seen in the paper doesn't continue indefinitely. A bowl shape curve was found for metabolic savings over the 10 force levels tested. 

The initial decrease in metabolic cost can be seen because of muscles such as the medial gastrocnemius and illiacus which are assisted by the device. Their activations go down as the assistive force from the exosuit goes up. Other muscles however, such as the tibialis anterior, are fighting against the device so their activation goes up with assistance level increasing metabolic cost. 

Exosuit Joint Tradeoff

The next question we investigated is if we are given a single actuator, how should we allocate assistive moments across the exosuit to cause the greatest reduction in metabolic cost?

Hip and Ankle

Hip, Knee and Ankle