8 citations · 13 across the 7 of their papers we have counts for
7 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…
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…
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…
Fusing uncalibrated IMUs and handheld smartphone video to reconstruct knee kinematics
J. D. Peiffer, Kunal Shah, Shawana Anarwala +2
Video and wearable sensor data provide complementary information about human movement. Video provides a holistic understanding of the entire body in the world while wearable sensor…
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…
Improved Trajectory Reconstruction for Markerless Pose Estimation
R. James Cotton, Anthony Cimorelli, Kunal Shah +3
Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, inc…