MSD-IRIMAS/DeepRehabPile
Deep Learning for Skeleton Based Human Motion Rehabilitation Assessment: A Benchmark
This project helps physical therapists and rehabilitation specialists objectively assess patient movement quality. By taking raw skeleton data from video — captured with common devices like smartphones or webcams — it provides an automated evaluation of how well a patient is performing rehabilitation exercises. This enables practitioners to track progress and identify subtle deviations from ideal motion more accurately than manual observation.
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Use this if you need a standardized, automated way to evaluate the quality of human motion during rehabilitation exercises, especially for research or developing new assessment tools.
Not ideal if you're looking for a direct, off-the-shelf software application for patient monitoring without any technical setup or development work.
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10
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Language
Python
License
GPL-3.0
Category
Last pushed
Aug 17, 2025
Commits (30d)
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