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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...
Autores principales: | Khataeipour, Seyed Javad, Anaraki, Javad Rahimipour, Bozorgi, Arastoo, Rayner, Machel, A Basset, Fabien, Fuller, Daniel |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
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Materias: | |
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 |
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