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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
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 |
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