ArticleNature medicine2021
Wearable sensor data and self-reported symptoms for COVID-19 detection.
Article in Nature medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05290792 (Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections), which is not on this map. Cited by 234 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections: The WE SENSE Study
Who cites it
234 citing papers in PubMed, 6 syntheses or guidelines pooled it, 472 citations in OpenAlex.
- Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review.JMIR mHealth and uHealth · 2024Pooled it
- Unsupervised home spirometryEuropean respiratory review : an official journal of the European Respiratory Society · 2023Pooled it
- IoT Adoption and Application for Smart Healthcare: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.The Cochrane database of systematic reviews · 2022Pooled it
- The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review.The Lancet. Digital health · 2022Pooled it
- Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Trial
- Feasibility of wearable sensor signals and self-reported symptoms to prompt at-home testing for acute respiratory viruses in the USA (DETECT-AHEAD): a decentralised, randomised controlled trial.The Lancet. Digital health · 2024Trial
- Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study.Journal of medical Internet research · 2023Trial
- Trial
- Using Statistical Time-Series Forecasting to Predict the Resting Heart Rate From Wearable Device Data: Case Report.JMIR formative research · 2026Article
- Implications of Wearable Sleep Health Technology for Cardiovascular Health Assessment and Interventions: A Narrative Review.Arteriosclerosis, thrombosis, and vascular biology · 2026Review
- A Structurally Robust Framework for Intelligent Graphene Thermometry via Few-Shot Transfer Learning and Algorithm-Hardware Co-Design.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Integrating Artificial Intelligence with Wearable Sensors for Advanced Health Monitoring and Diagnosis.Biosensors · 2026Review
- Cardiac rhythm development: A wearable device index of risk for physical and mental illness in adolescence.medRxiv : the preprint server for health sciences · 2026Article
- Sensor wide association studies in digital medicine.NPJ digital medicine · 2026Review
- A mixed-methods study comparing clinical and patient-reported perspectives on long COVID: insights from electronic health records and narrative journal entries.BMC infectious diseases · 2026Observational
- Evolutionary trajectory and knowledge structure of wearable devices for health management: A bibliometric analysis (1997-2025).Journal of family medicine and primary care · 2026Article
- Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis.Journal of medical Internet research · 2026Article
- Immune Ageing Clocks: A Methods-Oriented Review of Tasks, Modalities, Models, and Recalibration.Cells · 2026Review
174 more citing papers are in PubMed but not listed here.
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 2 institutions in 1 country.
Funding
Abstract
Traditional screening for COVID-19 typically includes survey questions about symptoms and travel history, as well as temperature measurements. Here, we explore whether personal sensor data collected over time may help identify subtle changes indicating an infection, such as in patients with COVID-19. We have developed a smartphone app that collects smartwatch and activity tracker data, as well as self-reported symptoms and diagnostic testing results, from individuals in the United States, and have assessed whether symptom and sensor data can differentiate COVID-19 positive versus negative cases in symptomatic individuals. We enrolled 30,529 participants between 25 March and 7 June 2020, of whom 3,811 reported symptoms. Of these symptomatic individuals, 54 reported testing positive and 279 negative for COVID-19. We found that a combination of symptom and sensor data resulted in an area under the curve (AUC) of 0.80 (interquartile range (IQR): 0.73-0.86) for discriminating between symptomatic individuals who were positive or negative for COVID-19, a performance that is significantly better (P < 0.01) than a model
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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.