An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study
- DOI
- 10.2196/43726
- Published
- 2023-03-07
- Container
- JMIR Biomedical Engineering
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2196/43726,
title = {An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study},
author = {Sara Popham and Maximilien Burq and Erin E Rainaldi and Sooyoon Shin and Jessilyn Dunn and Ritu Kapur},
year = {2023},
journal = {JMIR Biomedical Engineering},
doi = {10.2196/43726},
url = {https://doi.org/10.2196/43726}
}RIS
TY - JOUR TI - An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study AU - Sara Popham AU - Maximilien Burq AU - Erin E Rainaldi AU - Sooyoon Shin AU - Jessilyn Dunn AU - Ritu Kapur PY - 2023 JO - JMIR Biomedical Engineering DO - 10.2196/43726 UR - https://doi.org/10.2196/43726 ER -
APA
Popham, S., Burq, M., Rainaldi, E. E., Shin, S., Dunn, J., & Kapur, R. (2023). An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study. JMIR Biomedical Engineering. https://doi.org/10.2196/43726
Source records
- crossref · retrieved 2026-09-25T07:29:53.288Z