Capturing Real-World Habitual Sleep Patterns With a Novel User-Centric Algorithm to Preprocess Fitbit Data in the All of Us Research Program: Retrospective Observational Longitudinal Study
BackgroundCommercial wearables such as Fitbit quantify sleep metrics using fixed calendar times as default measurement periods, which may not adequately account for individual variations in sleep patterns. To address this limitation, experts in sleep medicine and wearable tec...
Saved in:
| Main Authors: | Hiral Master, Jeffrey Annis, Jack H Ching, Karla Gleichauf, Lide Han, Peyton Coleman, Kelsie M Full, Neil Zheng, Douglas Ruderfer, John Hernandez, Logan D Schneider, Evan L Brittain |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-07-01
|
| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e71718 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sensor-Based Frailty Assessment Using Fitbit
by: Mohammad Hosseinalizadeh, et al.
Published: (2024-12-01) -
Unlocking the potential of wearable technology: Fitbit-derived measures for predicting ADHD in adolescents
by: Muhammad Mahbubur Rahman, et al.
Published: (2025-05-01) -
Comprehensive comparison of Apple Watch and Fitbit monitors in a free-living setting.
by: Yang Bai, et al.
Published: (2021-01-01) -
Usability and Implementation Considerations of Fitbit and App Intervention for Diverse Cancer Survivors: Mixed Methods Study
by: Zakery Dabbagh, et al.
Published: (2025-02-01) -
Evaluating Fitbits for Assessment of Physical Activity and Sleep in Pediatric Pain: Feasibility and Acceptability Pilot Study
by: Bridget A Nestor, et al.
Published: (2025-07-01)