Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants

Current public health guidelines on physical activity and sleep duration are limited by a reliance on subjective self-reported evidence. Using data from simple wrist-worn activity monitors, we developed a tailored machine learning model, using balanced random forests with Hidden Markov Models, to re...

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Detalles Bibliográficos
Autores principales: Willetts, Matthew, Hollowell, Sven, Aslett, Louis, Holmes, Chris, Doherty, Aiden
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5962537/
https://www.ncbi.nlm.nih.gov/pubmed/29784928
http://dx.doi.org/10.1038/s41598-018-26174-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5962537/
https://www.ncbi.nlm.nih.gov/pubmed/29784928
http://dx.doi.org/10.1038/s41598-018-26174-1

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