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The Mobilize Center and Restore Center at Stanford University invite you to join our next webinar, featuring R. James Cotton from Shriley Ryan AbilityLab and Northwestern University.
DETAILS
Title: Clinically Accessible Movement Analysis using Single and Multiview Video
Speaker: R. James Cotton, MD, PhD, Shirley Ryan AbilityLab, Northwestern University
Time: Wednesday, June 25, 2025 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Markerless motion capture offers a promising path toward high-quality movement analysis in both clinical and research settings. However, translating video data into clinically meaningful insights requires not just ease of use, but also accuracy sufficient to capture clinically relevant outcomes and differences.
In the first part of the webinar, Dr. Cotton will discuss his lab’s recent advances in markerless motion capture that address these needs using both single-camera and multiview video approaches. Key to these advancements are high-performance biomechanical simulators (e.g., MuJoCo), which enables novel machine learning approaches to estimate kinematics and kinetics from different data sources. Dr. Cotton will explain the advantages of these simulators, how they compare to past approaches, and discuss the new opportunities they have given rise to in clinical applications. He will also discuss what large biomechanical datasets enable, such as imitation learning approaches to infer torques and muscle activations from kinematics, and even multimodal language models that answer clinically meaningful questions about movement.
In the second part of the webinar, Dr. Cotton will lead an interactive tutorial on fitting biomechanics from a sample monocular video using an end-to-end optimization based approach.
Cotton, R. J. (2024). Differentiable Biomechanics Unlocks Opportunities for Markerless Motion Capture. arXiv preprint arXiv:2402.17192.
DETAILS
Title: Clinically Accessible Movement Analysis using Single and Multiview Video
Speaker: R. James Cotton, MD, PhD, Shirley Ryan AbilityLab, Northwestern University
Time: Wednesday, June 25, 2025 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Markerless motion capture offers a promising path toward high-quality movement analysis in both clinical and research settings. However, translating video data into clinically meaningful insights requires not just ease of use, but also accuracy sufficient to capture clinically relevant outcomes and differences.
In the first part of the webinar, Dr. Cotton will discuss his lab’s recent advances in markerless motion capture that address these needs using both single-camera and multiview video approaches. Key to these advancements are high-performance biomechanical simulators (e.g., MuJoCo), which enables novel machine learning approaches to estimate kinematics and kinetics from different data sources. Dr. Cotton will explain the advantages of these simulators, how they compare to past approaches, and discuss the new opportunities they have given rise to in clinical applications. He will also discuss what large biomechanical datasets enable, such as imitation learning approaches to infer torques and muscle activations from kinematics, and even multimodal language models that answer clinically meaningful questions about movement.
In the second part of the webinar, Dr. Cotton will lead an interactive tutorial on fitting biomechanics from a sample monocular video using an end-to-end optimization based approach.
Cotton, R. J. (2024). Differentiable Biomechanics Unlocks Opportunities for Markerless Motion Capture. arXiv preprint arXiv:2402.17192.