Published on in Vol 7, No 6 (2019): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13384, first published .
Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors

Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors

Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors

Journals

  1. Liang Z, Ploderer B. How Does Fitbit Measure Brainwaves. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2020;4(1):1 View
  2. Louzon P, Andrews J, Torres X, Pyles E, Ali M, Du Y, Devlin J. Characterisation of ICU sleep by a commercially available activity tracker and its agreement with patient-perceived sleep quality. BMJ Open Respiratory Research 2020;7(1):e000572 View
  3. Guillodo E, Lemey C, Simonnet M, Walter M, Baca-García E, Masetti V, Moga S, Larsen M, Ropars J, Berrouiguet S. Clinical Applications of Mobile Health Wearable–Based Sleep Monitoring: Systematic Review. JMIR mHealth and uHealth 2020;8(4):e10733 View
  4. Thota D. Evaluating the Relationship Between Fitbit Sleep Data and Self-Reported Mood, Sleep, and Environmental Contextual Factors in Healthy Adults: Pilot Observational Cohort Study. JMIR Formative Research 2020;4(9):e18086 View
  5. Lunsford-Avery J, Keller C, Kollins S, Krystal A, Jackson L, Engelhard M. Feasibility and Acceptability of Wearable Sleep Electroencephalogram Device Use in Adolescents: Observational Study. JMIR mHealth and uHealth 2020;8(10):e20590 View
  6. Devine J, Chinoy E, Markwald R, Schwartz L, Hursh S. Validation of Zulu Watch against Polysomnography and Actigraphy for On-Wrist Sleep-Wake Determination and Sleep-Depth Estimation. Sensors 2020;21(1):76 View
  7. Mishra T, Wang M, Metwally A, Bogu G, Brooks A, Bahmani A, Alavi A, Celli A, Higgs E, Dagan-Rosenfeld O, Fay B, Kirkpatrick S, Kellogg R, Gibson M, Wang T, Hunting E, Mamic P, Ganz A, Rolnik B, Li X, Snyder M. Pre-symptomatic detection of COVID-19 from smartwatch data. Nature Biomedical Engineering 2020;4(12):1208 View
  8. Zhang Y, Folarin A, Sun S, Cummins N, Bendayan R, Ranjan Y, Rashid Z, Conde P, Stewart C, Laiou P, Matcham F, White K, Lamers F, Siddi S, Simblett S, Myin-Germeys I, Rintala A, Wykes T, Haro J, Penninx B, Narayan V, Hotopf M, Dobson R. Relationship Between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multicenter Longitudinal Observational Study. JMIR mHealth and uHealth 2021;9(4):e24604 View
  9. Rhee S, Kim C, Shin D, Steinhubl S. Present and Future of Digital Health in Diabetes and Metabolic Disease. Diabetes & Metabolism Journal 2020;44(6):819 View
  10. Liang Z, Chapa-Martell M. A Multi-Level Classification Approach for Sleep Stage Prediction With Processed Data Derived From Consumer Wearable Activity Trackers. Frontiers in Digital Health 2021;3 View