Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method

BACKGROUND: Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results. OBJECTIVE: Compare machine learning algorithms with standard methods (counts ratio) to i...

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Detalles Bibliográficos
Autores principales: Lum, Peter S., Shu, Liqi, Bochniewicz, Elaine M., Tran, Tan, Chang, Lin-Ching, Barth, Jessica, Dromerick, Alexander W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Original Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704838/
https://www.ncbi.nlm.nih.gov/pubmed/33150830
http://dx.doi.org/10.1177/1545968320962483

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704838/
https://www.ncbi.nlm.nih.gov/pubmed/33150830
http://dx.doi.org/10.1177/1545968320962483

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