ArticleSleep2021
Predicting circadian phase across populations: a comparison of mathematical models and wearable devices.
Article in Sleep, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 73 citations in OpenAlex.
- A circadian and app-based personalized lighting intervention for the reduction of cancer-related fatigue.Cell reports. Medicine · 2025Trial
- Trial
- Evaluating Wearable Devices for Remote Monitoring in Psychosis: Pilot Study Nested Within the CONNECT Cohort Study.JMIR formative research · 2026Article
- Design considerations for hypertension chronotherapy trials: insights from experience and modelling.BMC medicine · 2026Review
- Circadian Phase Estimation From Ambulatory Wearables With Particle Filtering: Accuracy Depends on Initialization, Recording Duration, and Light Exposure.Journal of biological rhythms · 2026Article
- Daily locomotor activity declines with tumor growth and disease progression in glioblastoma.JCI insight · 2026Article
- Circadian dimensions in insomnia disorder: mechanistic evidence, candidate phenotypes, and a phenotype-stratified research framework.Frontiers in psychiatry · 2026Article
- DCPR: a deep learning framework for circadian phase reconstruction.BMC bioinformatics · 2025Article
- The Association Between Race and Risk of COVID-19 Hospitalization: Examining the Contribution of Social Determinants of Health.Journal of racial and ethnic health disparities · 2025Article
- Article
- The relationship between sleep and circadian-sleep phase angles based on dim light melatonin onset predicted from light and activity data.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Tracking Daily Variations in Rest-Wake to Guide Personalized Timing of Temozolomide for High-Grade Glioma Patients.Journal of biological rhythms · 2025Article
- Afternoon to early evening bright light exposure reduces later melatonin production in adolescents.Npj biological timing and sleep · 2025Article
- Personalization of Cancer Treatment: Exploring the Role of Chronotherapy in Immune Checkpoint Inhibitor Efficacy.Cancers · 2025Review
- Wearables in Chronomedicine and Interpretation of Circadian Health.Diagnostics (Basel, Switzerland) · 2025Review
- The complexity and commonness of the two-process model of sleep regulation from a mathematical perspective.Npj biological timing and sleep · 2025Article
- Personal light treatment devices: a countermeasure to improve sleep, fatigue, and circadian misalignment in an operational setting.Sleep advances : a journal of the Sleep Research Society · 2025Article
- The real-world association between digital markers of circadian disruption and mental health risks.NPJ digital medicine · 2024Article
- Accurately predicting mood episodes in mood disorder patients using wearable sleep and circadian rhythm features.NPJ digital medicine · 2024Article
- Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study.JMIR public health and surveillance · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
From smart work scheduling to optimal drug timing, there is enormous potential in translating circadian rhythms research results for precision medicine in the real world. However, the pursuit of such effort requires the ability to accurately estimate circadian phase outside of the laboratory. One approach is to predict circadian phase noninvasively using light and activity measurements and mathematical models of the human circadian clock. Most mathematical models take light as an input and predict the effect of light on the human circadian system. However, consumer-grade wearables that are already owned by millions of individuals record activity instead of light, which prompts an evaluation of the accuracy of predicting circadian phase using motion alone. Here, we evaluate the ability of four different models of the human circadian clock to estimate circadian phase from data acquired by wrist-worn wearable devices. Multiple datasets across populations with varying degrees of circadian disruption were used for generalizability. Though the models we test yield similar predictions, analysis of data from 27 shift workers with high levels of circadian disruption shows that activity, which is recorded in almost every wearable device, is better at predicting circadian phase than measured light levels from wrist-worn devices when processed by mathematical models. In those living under normal living conditions, circadian phase can typically be predicted to within 1 h, even with data from a widely available commercial device (the Apple Watch). These results show that circadian phase can be predicted using existing data passively collected by millions of individuals with comparable accuracy to much more invasive and expensive methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.