5 papers
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 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…
Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone
J. D. Peiffer, Kunal Shah, Irina Djuraskovic +6
Movement directly reflects neurological and musculoskeletal health, yet objective biomechanical assessment is rarely available in routine care. We introduce Portable Biomechanics L…
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…