Validation of Azure Kinect for Upper Limb Motion Analysis Under Optimal and Suboptimal Conditions
Gabriele Fassina, Serena Cerfoglio, Michele Rigucci, Alessandra Pedrocchi, Veronica Cimolin, Emilia Ambrosini · 2026
Read Validation of Azure Kinect for Upper Limb Motion Analysis Under Optimal and Suboptimal Conditions by Gabriele Fassina, Serena Cerfoglio, Michele Rigucci, Alessandra Pedrocchi, Veronica Cimolin, Emilia Ambrosini (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13363823.txt.
Description
Gabriele Fassina and colleagues present a 2026 validation study of the Azure Kinect camera for tracking arm and shoulder movement in rehab settings. Marker-free cameras promise cheap, quick motion checks versus lab systems with body markers. Sixteen healthy adults performed ten upper-body tasks in three setups: ideal, seated with a table blocking the view, and a longer camera distance, while a gold-standard light system recorded the truth.
The camera tracked movements in its own plane well, with error staying low even in the awkward setups. Movements toward or away from the camera fared poorly. Range of motion reads were solid and repeatable, but timing and smoothness scores strayed. The authors advise care with camera placement and further tests in patients.
Catalog record
| CREATOR | Gabriele Fassina, Serena Cerfoglio, Michele Rigucci, Alessandra Pedrocchi, Veronica Cimolin, Emilia Ambrosini |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 71475 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |