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

Sara Popham, Maximilien Burq, Erin E Rainaldi, Sooyoon Shin, Jessilyn Dunn, Ritu Kapur

Open source

DOI
10.2196/43726
Published
2023-03-07
Container
JMIR Biomedical Engineering
Publisher
JMIR Publications Inc.
Open access
unknown

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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

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