Accessibility settings

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

New Methods (1191) Tools, Programs and Algorithms (417) mHealth for Data Collection and Research (1277) Wearable Devices and Sensors (1228) Insomnia and Sleep Hygiene (263) Secondary Use of Clinical Data for Research and Surveillance (500) Sleep Monitoring, Sleep Quality, Sleep Disorders (288)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71718, first published .
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

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

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

Authors of this article:

Hiral Master1 Author Orcid Image ;   Jeffrey Annis1 Author Orcid Image ;   Jack H Ching2 Author Orcid Image ;   Karla Gleichauf2 Author Orcid Image ;   Lide Han1 Author Orcid Image ;   Peyton Coleman1 Author Orcid Image ;   Kelsie M Full1 Author Orcid Image ;   Neil Zheng3 Author Orcid Image ;   Douglas Ruderfer1 Author Orcid Image ;   John Hernandez2 Author Orcid Image ;   Logan D Schneider2 Author Orcid Image ;   Evan L Brittain1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Jeong H, Katta S, Wang W, Volfovsky A, Dunn J. Impact of daylight saving time on physical activity patterns. Nature Health 2026 View