Predicting lying, sitting and walking at different intensities using smartphone accelerometers at three different wear locations: hands, pant pockets, backpack

OBJECTIVE: This study uses machine learning (ML) to develop methods for estimating activity type/intensity using smartphones, to evaluate the accuracy of these models for classifying activity, and to evaluate differences in accuracy between three different wear locations. METHOD: Forty-eight partici...

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Detalles Bibliográficos
Autores principales: Khataeipour, Seyed Javad, Anaraki, Javad Rahimipour, Bozorgi, Arastoo, Rayner, Machel, A Basset, Fabien, Fuller, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9086604/
https://www.ncbi.nlm.nih.gov/pubmed/35601137
http://dx.doi.org/10.1136/bmjsem-2021-001242

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9086604/
https://www.ncbi.nlm.nih.gov/pubmed/35601137
http://dx.doi.org/10.1136/bmjsem-2021-001242

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