Concurrent validity of machine learning-classified functional upper extremity use from accelerometry in chronic stroke

Objective: This study aims to investigate the validity of machine learning-derived amount of real-world functional upper extremity (UE) use in individuals with stroke. We hypothesized that machine learning classification of wrist-worn accelerometry will be as accurate as frame-by-frame video labelin...

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Detalles Bibliográficos
Autores principales: Geed, Shashwati, Grainger, Megan L., Mitchell, Abigail, Anderson, Cassidy C., Schmaulfuss, Henrike L., Culp, Seraphina A., McCormick, Eilis R., McGarry, Maureen R., Delgado, Mystee N., Noccioli, Allysa D., Shelepov, Julia, Dromerick, Alexander W., Lum, Peter S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073694/
https://www.ncbi.nlm.nih.gov/pubmed/37035665
http://dx.doi.org/10.3389/fphys.2023.1116878

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073694/
https://www.ncbi.nlm.nih.gov/pubmed/37035665
http://dx.doi.org/10.3389/fphys.2023.1116878

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