AIGaitor is the first claimed end-to-end on-device monocular motion-capture and deep-learning gait analysis pipeline demonstrated on consumer smartphones.
Interrater reliability of videotaped observational gait-analysis assessments
2 Pith papers cite this work. Polarity classification is still indexing.
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Markerless pipeline estimates Rodda-Graham knee (R²=0.80) and ankle (R²=0.57) z-scores from single-view videos in 152 children with 60 diagnoses, achieving AUROC=0.88 for excess knee flexion screening.
citing papers explorer
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AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing
AIGaitor is the first claimed end-to-end on-device monocular motion-capture and deep-learning gait analysis pipeline demonstrated on consumer smartphones.
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Quantifying Rodda and Graham Gait Classification from 3D Markerless Kinematics derived from a Single-view Video in a Heterogeneous Pediatric Clinical Cohort
Markerless pipeline estimates Rodda-Graham knee (R²=0.80) and ankle (R²=0.57) z-scores from single-view videos in 152 children with 60 diagnoses, achieving AUROC=0.88 for excess knee flexion screening.