Machine Learning to Quantify Physical Activity in Children with Cerebral Palsy: Comparison of Group, Group-Personalized, and Fully-Personalized Activity Classification Models

Pattern recognition methodologies, such as those utilizing machine learning (ML) approaches, have the potential to improve the accuracy and versatility of accelerometer-based assessments of physical activity (PA). Children with cerebral palsy (CP) exhibit significant heterogeneity in relation to imp...

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Detalles Bibliográficos
Autores principales: Ahmadi, Matthew N., O’Neil, Margaret E., Baque, Emmah, Boyd, Roslyn N., Trost, Stewart G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411900/
https://www.ncbi.nlm.nih.gov/pubmed/32708963
http://dx.doi.org/10.3390/s20143976

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411900/
https://www.ncbi.nlm.nih.gov/pubmed/32708963
http://dx.doi.org/10.3390/s20143976

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