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

Biomedical Engineering Articles (54) Innovations and Technology for Physical Activity Education (537) Wearable Devices and Sensors (657) Fitness Trackers and Smart Pedometers/Accelerometers (492)

Published on in Vol 8 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43726, first published .
An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

Authors of this article:

Sara Popham 1 Author Orcid Image ;   Maximilien Burq 1 Author Orcid Image ;   Erin E Rainaldi 1 Author Orcid Image ;   Sooyoon Shin 1 Author Orcid Image ;   Jessilyn Dunn 2, 3, 4 Author Orcid Image ;   Ritu Kapur 1 Author Orcid Image
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