Details
- Title: OpenCap – Analyzing 3D Human Movement Dynamics using Smartphone Videos
- Speakers: Scott Uhlrich, PhD, & Antoine Falisse, PhD, Stanford University
- Time: Tuesday, October 25th, 2022 at 9:00 AM Pacific Time
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Abstract
Measures of human movement and the forces that underlie it can predict injuries and inform rehabilitation. Analyzing these quantities in a motion capture laboratory is time intensive and costly, limiting high-fidelity biomechanical analysis to small-scale research studies. Scalable tools for analyzing human movement dynamics are needed. To address this, Drs. Uhlrich and Falisse developed OpenCap, a freely-available, cloud-based tool that measures both human movement kinematics (i.e., joint angles), and kinetics (e.g., muscle activations, ground reaction forces, and joint loading) using two smartphones. OpenCap measures these quantities 25 times faster and at less than 1% of the cost of laboratory-based motion capture.
In the first half of the webinar, Drs. Uhlrich and Falisse will present their validation of OpenCap. They will demonstrate how OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions.
In the tutorial during the second half of the webinar, Drs. Uhlrich and Falisse will share how to set up a collection, access kinematic measures, generate dynamic simulations, and understand the strengths and limitations of OpenCap.
Uhlrich, S. D., Falisse, A., Kidziński, Ł., Muccini, J., Ko, M., Chaudhari, A. S., Hicks, J.L., & Delp, S. L. (2022). OpenCap: 3D human movement dynamics from smartphone videos. bioRxiv.
This webinar is offered jointly with the Restore Center, an NIH-funded Medical Rehabilitation Research Resource Network Center at Stanford University.
About Our Speakers
Scott Uhlrich, PhD
Research Engineer
Dr. Scott Uhlrich is the Director of Research in the Stanford Human Performance Lab. He combines experimental techniques, biomechanical modeling, and machine learning to develop tools for preventing injury, improving the efficacy of rehabilitation, and maximizing mobility for individuals with diseases like osteoarthritis. Dr. Uhlrich has designed and patented numerous rehabilitation tools and has investigated their efficacy in clinical trials. He also develops tools for measuring human movement with commodity sensors like a cell phone camera, facilitating clinically-actionable measurements to be made in the clinic, at home, or on the field.
Dr. Uhlrich received his PhD from Stanford University, where he designed and evaluated several gait modifications to reduce joint loading for individuals with knee osteoarthritis. Dr. Uhlrich received several awards during his PhD, including a National Science Foundation graduate research fellowship, a Stanford Graduate Fellowship, and the Young Investigator Award from the Osteoarthritis Research Society International.
Antoine Falisse, PhD
Postdoctoral Fellow
Dr. Antoine Falisse is a postdoctoral fellow in Bioengineering working on computational approaches to study human movement disorders. He primarily uses optimization methods, machine learning, biomechanical modeling, and data from various sources (wearables, videos, medical images) to get insights into movement abnormalities and improve treatments and rehabilitation protocols.
Dr. Falisse received his PhD from KU Leuven (Belgium) where he worked on modeling and simulating the locomotion of children with cerebral palsy. His research was supported by the Research Foundation Flanders (FWO) through a personal fellowship. Dr. Falisse received several awards for his PhD work, including the David Winter Young Investigator Award, the Andrzej J. Komor Young Investigator Award, the VPHi Thesis Award in In Silico Medicine, and the KU Leuven Research Council Award in Biomedical Sciences.
