8 citations · 12 across the 16 of their papers we have counts for
8 papers · 1 filter
Cross-Model Distillation of a Human-Pose Foundation Model from Unannotated Infant Video for Markerless 3D Pose Estimation
R. James Cotton, Divya Joshi, Colleen Peyton
Spontaneous movement is one of the earliest windows onto an infant's neuromotor health, and structured clinical instruments that score it are validated early predictors of cerebral…
Biomechanical 3D Body: Self-Supervised Distillation of Biomechanical Pose from a 3D Body Foundation Model
R. James Cotton, J. D. Peiffer, Lucinda Williamson +2
State-of-the-art monocular body recovery methods predict mesh vertices and angles on the corresponding kinematic tree, but their outputs lack biomechanically defined joint angles t…
Markerless Motion Capture in Routine Clinical Upper Limb Assessments: Validity and Insights Beyond Ordinal Scoring
Tim Unger, Olivier Lambercy, Roger Gassert +3
The Action Research Arm Test (ARAT) is a widely-used upper limb outcome measure in neurorehabilitation, but its ordinal scoring is subjective and suffers from limited sensitivity a…
Biomechanics-aware Multi-view Markerless Motion Capture of Dexterous Hand Movements
Pouyan Firouzabadi, J. D. Peiffer, Kunal Shah +4
Markerless motion capture (MMC) techniques have been widely beneficial in biomechanical analysis of human movement; however, application to complex motions of the hand lags other m…
Markerless Motion Capture for Biomechanical Whole-Body Kinematic Estimation in Infants
Divya Joshi, J. D. Peiffer, Colleen Peyton +1
arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated, objective alternatives. One…
Monocular Biomechanical Tracking of Fingers with Inverse Kinematics to Foundation Models
R. James Cotton, Pouyan Firouzabadi, Wendy Murray
Accurate hand and finger tracking from video has significant clinical applications for monitoring activities of daily living and measuring range of motion, yet monocular video appr…
Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace
Seth Donahue, J. D. Peiffer, R. Tyler Richardson +7
To validate a clinically accessible approach for quantifying the Upper Extremity Reachable Workspace (UERW) using a single (monocular) camera and Artificial Intelligence (AI)-drive…
Calibrated Uncertainty for Trustworthy Clinical Gait Analysis Using Probabilistic Multiview Markerless Motion Capture
Seth Donahue, Irina Djuraskovic, Kunal Shah +3
Video-based human movement analysis holds potential for movement assessment in clinical practice and research. However, the clinical implementation and trust of multi-view markerle…