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The Mobilize and FAIR Centers at Stanford University invite you to join our next webinar, featuring Parker Ruth from Stanford University.
DETAILS
Title: Accelerating Biomarker Discovery through Large-Scale Motion Capture Using OpenCap
Speaker: Parker Ruth, Department of Computer Science, Stanford University
Time: Wednesday, June 24, 2026 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Markerless motion capture technologies like OpenCap can expand opportunities for collecting human motion datasets outside the limitations of traditional motion capture laboratories. Parker Ruth and colleagues from the Stanford Neuromuscular Biomechanics Lab have used OpenCap to conduct large-scale human movement data collection events to develop more quantitative and sensitive outcome measures for neuromuscular diseases, including myotonic dystrophy, facioscapulohumeral muscular dystrophy, and Charcot-Marie-Tooth disease. Large-scale data collections have allowed them to record a battery of nine activities from up to one hundred participants in one weekend, leading to the largest biomechanics datasets for these diseases to date.
In this two-part webinar, Mr. Ruth will share his team’s process and best practices gained from the past three years of large-scale OpenCap data collection.
In the first part, he will describe the latest findings from their large-scale study of neuromuscular disease biomechanics. He will share how these findings emerged from their fruitful collaboration with neurology and physical therapy experts to collaboratively conceive the study and develop domain-informed and interpretable data representations.
In the second part, he will share a process and best practices for planning similar large-scale human movement data collection events with OpenCap, including study design, logistics, and data management and sharing.
Ruth, P. S., Uhlrich, S. D., de Monts, C., Falisse, A., Muccini, J., Covitz, S., Vogt-Domke, S., Day, J., Duong, T., & Delp, S. L. (2025). Video-Based Biomechanical Analysis Captures Disease-Specific Movement Signatures of Different Neuromuscular Diseases. New England Journal of Medicine AI, 2(9).
DETAILS
Title: Accelerating Biomarker Discovery through Large-Scale Motion Capture Using OpenCap
Speaker: Parker Ruth, Department of Computer Science, Stanford University
Time: Wednesday, June 24, 2026 at 9:00 AM Pacific Time
Registration: Click here to register
ABSTRACT
Markerless motion capture technologies like OpenCap can expand opportunities for collecting human motion datasets outside the limitations of traditional motion capture laboratories. Parker Ruth and colleagues from the Stanford Neuromuscular Biomechanics Lab have used OpenCap to conduct large-scale human movement data collection events to develop more quantitative and sensitive outcome measures for neuromuscular diseases, including myotonic dystrophy, facioscapulohumeral muscular dystrophy, and Charcot-Marie-Tooth disease. Large-scale data collections have allowed them to record a battery of nine activities from up to one hundred participants in one weekend, leading to the largest biomechanics datasets for these diseases to date.
In this two-part webinar, Mr. Ruth will share his team’s process and best practices gained from the past three years of large-scale OpenCap data collection.
In the first part, he will describe the latest findings from their large-scale study of neuromuscular disease biomechanics. He will share how these findings emerged from their fruitful collaboration with neurology and physical therapy experts to collaboratively conceive the study and develop domain-informed and interpretable data representations.
In the second part, he will share a process and best practices for planning similar large-scale human movement data collection events with OpenCap, including study design, logistics, and data management and sharing.
Ruth, P. S., Uhlrich, S. D., de Monts, C., Falisse, A., Muccini, J., Covitz, S., Vogt-Domke, S., Day, J., Duong, T., & Delp, S. L. (2025). Video-Based Biomechanical Analysis Captures Disease-Specific Movement Signatures of Different Neuromuscular Diseases. New England Journal of Medicine AI, 2(9).