The paper presents AIGaitor, a privacy-preserving on-device monocular motion analysis system that performs end-to-end pose estimation and deep learning gait analysis on consumer smartphones.
An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients
2 Pith papers cite this work. Polarity classification is still indexing.
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Markerless single-view video pipeline estimates Rodda and Graham knee and ankle z-scores in a heterogeneous pediatric cohort of 152 children, achieving R²=0.80 for knee and R²=0.57 for ankle versus 3D-IGA ground truth.
citing papers explorer
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AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing
The paper presents AIGaitor, a privacy-preserving on-device monocular motion analysis system that performs end-to-end pose estimation and deep learning gait analysis on consumer smartphones.
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Quantifying Rodda and Graham Gait Classification from 3D Makerless Kinematics derived from a Single-view Video in a Heterogeneous Pediatric Clinical Cohort
Markerless single-view video pipeline estimates Rodda and Graham knee and ankle z-scores in a heterogeneous pediatric cohort of 152 children, achieving R²=0.80 for knee and R²=0.57 for ankle versus 3D-IGA ground truth.