4 citations · 5 across the 3 of their papers we have counts for
3 papers
Differentiable Biomechanics for Markerless Motion Capture in Upper Limb Stroke Rehabilitation: A Comparison with Optical Motion Capture
Tim Unger, Arash Sal Moslehian, J. D. Peiffer +5
Marker-based Optical Motion Capture (OMC) paired with biomechanical modeling is currently considered the most precise and accurate method for measuring human movement kinematics. H…
Self-Supervised Learning of Gait-Based Biomarkers
R. James Cotton, J. D. Peiffer, Kunal Shah +5
Markerless motion capture (MMC) is revolutionizing gait analysis in clinical settings by making it more accessible, raising the question of how to extract the most clinically meani…
Markerless Motion Capture and Biomechanical Analysis Pipeline
R. James Cotton, Allison DeLillo, Anthony Cimorelli +5
Markerless motion capture using computer vision and human pose estimation (HPE) has the potential to expand access to precise movement analysis. This could greatly benefit rehabili…