Our tools and training help researchers produce insights from wearables, video, medical images, and other data sources

Software for Biomechanical Modeling and Machine Learning

Our open-source tools enable individuals to easily incorporate our methods into their research

Data Sharing Communities

We provide infrastructure and personnel to create data collections and communities to advance movement research and method development

Training Opportunities

Our webinars, workshops, and symposia provide knowledge, skills, and networking opportunities for both novices and experts

A Biomedical Technology Resource Center funded by the National Institutes of Health and based at Stanford University

Research Highlights

Our collaborating projects drive the development of our software tools. See all projects.
Developing Video-Based Biomarkers for Facioscapulohumeral Muscular Dystrophy and Myotonic Dystrophy

Developing Video-Based Biomarkers for Facioscapulohumeral Muscular Dystrophy and Myotonic Dystrophy

We are collaborating with Dr. John Day to discover movement biomarkers for neuromuscular disease using smartphone video. The goal of the project is to extract biomechanical features that are clinic ready.

Personalized Assessment and Treatment of Patellar Instability Enabled Through Machine Learning

Personalized Assessment and Treatment of Patellar Instability Enabled Through Machine Learning

We are collaborating with Drs. Beth Shubin Stein and Shital Parikh to develop machine learning approaches that will enable the exploration of factors and treatment of patellar instability.

Digital Biomarkers of Post-traumatic Osteoarthritis: Toward Precision Rehabilitation

Digital Biomarkers of Post-traumatic Osteoarthritis: Toward Precision Rehabilitation

We are collaborating with Dr. Eni Halilaj to developing new wearable sensing and computer vision algorithms to passively monitor physical therapy and gait biomechanics after ACL reconstruction.

News & Events

Webinar: Muscle-Driven Simulations and Experimental Data of Cycling

In the first half of the webinar, Ms. Clancy will present her OpenSim modeling pipeline for cycling and the results of her study. In the second half, she will discuss best practices for and share lessons learned from working with OpenSim Moco, including strategies for refining Moco optimization problems.