The effect of depth data and upper limb impairment on lightweight monocular RGB human pose estimation models

The effect of depth data and upper limb impairment on lightweight monocular RGB human pose estimation models

Abstract Background and objectives Markerless vision-based human pose estimation (HPE) is a promising avenue towards scalable data collection in rehabilitation. Deploying this technology will require self-contained systems able to process data efficiently and accurately. The aims of this work are to...

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Bibliographic Details
Main Authors: Gloria-Edith Boudreault-Morales, Cesar Marquez-Chin, Xilin Liu, José Zariffa
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BioMedical Engineering OnLine
Subjects:
Pose estimation
Depth data
Motion capture
Rehabilitation
Stroke
Online Access:https://doi.org/10.1186/s12938-025-01347-y
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