[Opensim-announcement] Webinar on Bone and Joint Shape Modeling in Musculoskeletal Models, Gait Foundation Model Demo

[Matthew Petrucci]

Webinar on Bone and Joint Shape Modeling in Musculoskeletal Models

Wednesday, October 29, 2025 at 9:00 AM PDT


We are pleased to announce our upcoming webinar with Allison Clouthier, PhD from the University of Ottawa and Erin Lee, PhD from the University of Waterloo, entitled “Integrating Bone and Joint Geometry into Musculoskeletal Models.”



Certain bone and joint shape features are linked to injury risk and disease severity, but these associations fail to explain how individual bone shapes impact those conditions and their treatment. In this webinar, Dr. Lee and Dr. Clouthier will discuss how incorporating joint geometry into musculoskeletal models can reveal insights about the relationship between certain bone features and increased injury risk. They will also lead an interactive tutorial demonstrating how to map soft tissue attachment sites across bone geometries using statistical shape models and incorporate those sites into a musculoskeletal model. This event will be hosted jointly by the Mobilize<http://mobilize.stanford.edu> and Restore<http://restore.stanford.edu/> Centers. Learn more and register<https://mobilize.stanford.edu/webinar-integrating-bone-and-joint-geometry-into-musculoskeletal-models/> | Read the paper<https://doi.org/10.1016/j.medengphy.2019.02.009>


Demo Available for GaitDynamics, a Generative Foundation Model for Analyzing Human Walking and Running


Data driven-models are a promising solution to quantify gait dynamics with less cost and time compared with traditional lab-based experiments. Typical data-driven models are limited to a specific downstream task with fixed inputs and outputs. GaitDynamics is the first generative foundation model to quantify gait dynamics for different gait patterns. It is a flexible, scalable solution that is able to predict both motions and forces for human walking and running with partial or no input data. Postdoctoral fellow Tian Tan and colleagues from the NIH-funded Restore<http://restore.stanford.edu> and Mobilize<http://mobilize.stanford.edu> Centers and the Wu Tsai Human Performance Alliance<https://humanperformancealliance.org/> developed the model and have made it open-source, now including a HuggingFace demo to test with your own data. Try Demo<https://huggingface.co/spaces/alanttan/GaitDynamics> | Access GaitDynamics code<https://github.com/stanfordnmbl/GaitDynamics> | Read preprint<https://pmc.ncbi.nlm.nih.gov/articles/PMC11957236/>






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OpenSim is supported by the Mobilize Center<https://mobilize.stanford.edu/>, an NIH Biomedical Technology Resource Center (grant P41 EB027060); the Restore Center<https://restore.stanford.edu/>, an NIH-funded Medical Rehabilitation Research Resource Network Center (grant P2C HD101913); and the Wu Tsai Human Performance Alliance <https://humanperformancealliance.org/> through the Joe and Clara Tsai Foundation.





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