Random forest algorithms for recognizing daily life activities using plantar pressure information: a smart-shoe study

BACKGROUND: Wearable activity trackers are regarded as a new opportunity to deliver health promotion interventions. Indeed, while the prediction of active behaviors is currently primarily relying on the processing of accelerometer sensor data, the emergence of smart clothes with multi-sensing capaci...

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Detalles Bibliográficos
Autores principales: Ren, Dian, Aubert-Kato, Nathanael, Anzai, Emi, Ohta, Yuji, Tripette, Julien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Anatomy and Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602692/
https://www.ncbi.nlm.nih.gov/pubmed/33194400
http://dx.doi.org/10.7717/peerj.10170

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602692/
https://www.ncbi.nlm.nih.gov/pubmed/33194400
http://dx.doi.org/10.7717/peerj.10170

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