This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3278) Machine Learning (2097) Fitness Trackers and Smart Pedometers/Accelerometers (673) Wearable Devices and Sensors (1151)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71969, first published .
Recognizing Skateboard and Kickboard Commuting Behaviors Using Activity Trackers: Feasibility Study Using Machine Learning Approaches

Recognizing Skateboard and Kickboard Commuting Behaviors Using Activity Trackers: Feasibility Study Using Machine Learning Approaches

Recognizing Skateboard and Kickboard Commuting Behaviors Using Activity Trackers: Feasibility Study Using Machine Learning Approaches

Authors of this article:

Nathanael Aubert-Kato1, 2 Author Orcid Image ;   Hitomi Hatori3 Author Orcid Image ;   Arisa Orihara3 Author Orcid Image ;   Takashi Nakagata4, 5 Author Orcid Image ;   Yuji Ohta3 Author Orcid Image ;   Julien Tripette2, 3 Author Orcid Image
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