Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace

This study validates a clinically accessible approach for quantifying the Upper Extremity Reachable Workspace (UERW) using monocular AI-driven Markerless Motion Capture (MMC). Objective validation of such techniques for clinically oriented tasks is essential to support their adoption in clinical mot...

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Bibliografski detalji

Glavni autori:	Seth Donahue, J.D. Peiffer, R. Tyler Richardson, Yishan Zhong, Shaun Q. Y. Tan, Benoit L. Marteau, Stephanie A. Russo, May D. Wang, R. James Cotton, Ross Chafetz
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2026-05-01
Serija:	Sensors
Teme:	reachable workspace Markerless Motion Capture monocular camera clinical feasibility artificial intelligence
Online pristup:	https://www.mdpi.com/1424-8220/26/11/3421
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