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 capacit...

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Bibliographic Details
Main Authors: Dian Ren, Nathanael Aubert-Kato, Emi Anzai, Yuji Ohta, Julien Tripette
Format: Article
Language:English
Published: PeerJ Inc. 2020-10-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/10170.pdf