Collaborative projects (CPs) drive the development of our computational models and tools. They help us identify technological needs within the bioengineering, biomechanical modeling, data science, mHealth, and rehabilitation research communities. We work with them to define the specifications for tools to address those needs, and they serve as beta testers to refine and harden the tools we develop and share through extensive two-way collaboration.
Our current CPs are:
- Optimization of Exoskeleton Assistance Using Wearable Sensors
- PI: Steve Collins, Stanford University
- Personalized Assessment and Treatment of Patellar Instability Enabled Through Machine Learning
- PIs: Shital Parikh, Beth Shubin Stein, University of Cincinnati
- Using Video and Wearable Sensor Data for Fall Prevention in Older Adults
- PIs: Women’s Health Initiative
- Measuring Knee Adduction Moment Pre and Post Intervention using OpenCap
- PI: Constance Chu, Stanford University
- Digital Biomarkers of Post-traumatic Osteoarthritis: Toward Precision Rehabilitation
- PI: Eni Halilaj, Carnegie Mellon University
- Developing video-based biomarkers for facioscapulohumeral muscular dystrophy and myotonic dystrophy
- PI: John Day, Stanford University
Graduated CPs:
- Prediction of Freezing of Gait from Neural Recordings and IMU Data
- PI: Helen Bronte-Stewart, Stanford University
- Personalized Gait Retraining for Individuals with Osteoarthritis
- PI: Julie Kolesar, VA Palo Alto Health Care System
- Estimating Bone Loading via Wearable Sensors in Children with Cerebral Palsy
- PI: Tishya Wren, Children’s Hospital Los Angeles
- Patterns of Asymmetry and Energy Cost Generated from Predictive Simulations of Hemiparetic Gait
- PI: James Finley, University of Southern California
Have a project you think would be a great CP? Please fill out this Google form or contact us at mobilize-center@stanford.edu.