Assessing Upper Limb Function in Breast Cancer Survivors Using Wearable Sensors and Machine Learning in a Free-Living Environment

(1) Background: Being able to objectively assess upper limb (UL) dysfunction in breast cancer survivors (BCS) is an emerging issue. This study aims to determine the accuracy of a pre-trained lab-based machine learning model (MLM) to distinguish functional from non-functional arm movements in a home...

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Detalles Bibliográficos
Autores principales: Vets, Nieke, De Groef, An, Verbeelen, Kaat, Devoogdt, Nele, Smeets, Ann, Van Assche, Dieter, De Baets, Liesbet, Emmerzaal, Jill
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347074/
https://www.ncbi.nlm.nih.gov/pubmed/37447951
http://dx.doi.org/10.3390/s23136100

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347074/
https://www.ncbi.nlm.nih.gov/pubmed/37447951
http://dx.doi.org/10.3390/s23136100

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