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Fusing uncalibrated IMUs and handheld smartphone video to reconstruct knee kinematics
Reconstructing from a fusion of video and wearable sensor data further reduces this error.
Self-Supervised Learning of Gait-Based Biomarkers
We find that contrastive learning on unannotated gait data learns a representation that captures clinically meaningful information.
Markerless Motion Capture and Biomechanical Analysis Pipeline
Markerless motion capture using computer vision and human pose estimation (HPE) has the potential to expand access to precise movement analysis.
Improved Trajectory Reconstruction for Markerless Pose Estimation
Markerless pose estimation allows reconstructing human movement from multiple synchronized and calibrated views, and has the potential to make movement analysis easy and quick, including gait analysis.
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