Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach

The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the utility of both K-means clustering and agglomerat...

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Detalles Bibliográficos
Autores principales: Pontin, Francesca, Lomax, Nik, Clarke, Graham, Morris, Michelle A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8583116/
https://www.ncbi.nlm.nih.gov/pubmed/34769991
http://dx.doi.org/10.3390/ijerph182111476

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8583116/
https://www.ncbi.nlm.nih.gov/pubmed/34769991
http://dx.doi.org/10.3390/ijerph182111476

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