Cailtin Clancy from Stanford University presents her OpenSim modeling pipeline for cycling and the results of her study. She demonstrates her team’s approach to generating simulations using OpenSim Moco and how they explored different optimization objectives to improve similarity with experimental data. Her team found that adding a term in the objective function that minimized tibiofemoral joint reaction forces preserved cycling power and kinematics, which improved similarity with experimental data. The musculoskeletal models, muscle-driven simulations, simulations software, and experimental data are freely available at https://simtk.org/projects/cycling_sim.

This webinar is offered jointly with the Restore Center (https://restore.stanford.edu/), an NIH-funded Medical Rehabilitation Research Resource Network Center at Stanford University.

Watch the tutorial:
   • Webinar: Muscle-Driven Simulations an...  

Learn more:
Read the associated publications:
https://doi.org/10.1038/s41598-023-47...
Download the data and pipeline:
https://simtk.org/projects/cycling_sim

0:00 Intro
3:12 Motivation
6:21 Modeling Pipeline
10:53 Key Results
18:18 Q&A