ArticleScientific reports2022
Real-time infection prediction with wearable physiological monitoring and AI to aid military workforce readiness during COVID-19.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 66 citations in OpenAlex.
- Increasing Use of Wearable Devices for Health or Activity Tracking Among Adults with Chronic Diseases in the US.Journal of the American College of Surgeons · 2026Article
- Wearable-derived skin temperature dynamics during sleep reveal cardiovascular perfusion deficits through mechanistic modeling.NPJ digital medicine · 2026Article
- Editorial: Invisible hazards, lasting impact: airborne toxicants and systemic disease from environmental and occupational exposures.Frontiers in public health · 2026Article
- Smart Ring in Clinical Medicine: A Systematic Review.Biomimetics (Basel, Switzerland) · 2025Review
- American Life in Realtime: Benchmark, publicly available person-generated health data for equity in precision health.PNAS nexus · 2025Article
- An infection prediction model developed from inpatient data can predict out-of-hospital COVID-19 infections from wearable data when controlled for dataset shift.Scientific reports · 2025Article
- Automatic detection of persistent physiological changes after COVID infection via wearable devices with potential for long COVID management.Scientific reports · 2025Article
- Wearable-derived short sleep duration is associated with higher C-reactive protein in a placebo-controlled vaccine trial among young adults.Scientific reports · 2025Article
- Timing is survival: modeling how earlier calls improve cardiac arrest outcomes.Frontiers in digital health · 2025Article
- Real-time monitoring of military health and readiness: a perspective on future research.Frontiers in digital health · 2025Article
- Intensive, Real-Time Data Collection of Psychological and Physiological Stress During a 96-Hour Field Training Exercise at a Senior Military College: Feasibility and Acceptability Cohort Study.JMIR formative research · 2024Article
- Approaches for the Use of AI in Workplace Health Promotion and Prevention: Systematic Scoping Review.JMIR AI · 2024Article
- Study of Postacute Sequelae of COVID-19 Using Digital Wearables: Protocol for a Prospective Longitudinal Observational Study.JMIR research protocols · 2024Observational
- Continuous Monitoring of Heart Rate Variability in Free-Living Conditions Using Wearable Sensors: Exploratory Observational Study.JMIR formative research · 2024Article
- Detection of Common Respiratory Infections, Including COVID-19, Using Consumer Wearable Devices in Health Care Workers: Prospective Model Validation Study.JMIR formative research · 2024Article
- Acceptable nudge strategies to incentivize the use of wearables and physiolytics at work: A Q-methodology examination.Journal of information technology : JIT · 2024Article
- Utilizing Wearable Device Data for Syndromic Surveillance: A Fever Detection Approach.Sensors (Basel, Switzerland) · 2024Article
- Sex-specific differences in physiological parameters related to SARS-CoV-2 infections among a national cohort (COVI-GAPP study).PloS one · 2024Article
- A prospective natural history study of post acute sequalae of COVID-19 using digital wearables: Study protocol.Research square · 2023Article
- Understanding the leading indicators of hospital admissions from COVID-19 across successive waves in the UK.Epidemiology and infection · 2023Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
Abstract
Infectious threats, like the COVID-19 pandemic, hinder maintenance of a productive and healthy workforce. If subtle physiological changes precede overt illness, then proactive isolation and testing can reduce labor force impacts. This study hypothesized that an early infection warning service based on wearable physiological monitoring and predictive models created with machine learning could be developed and deployed. We developed a prototype tool, first deployed June 23, 2020, that delivered continuously updated scores of infection risk for SARS-CoV-2 through April 8, 2021. Data were acquired from 9381 United States Department of Defense (US DoD) personnel wearing Garmin and Oura devices, totaling 599,174 user-days of service and 201 million hours of data. There were 491 COVID-19 positive cases. A predictive algorithm identified infection before diagnostic testing with an AUC of 0.82. Barriers to implementation included adequate data capture (at least 48% data was needed) and delays in data transmission. We observe increased risk scores as early as 6 days prior to diagnostic testing (2.3 days average). This study showed feasibility of a real-time risk prediction score to minimize workforce impacts of infection.
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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.