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

Non-randomized Protocols and Methods (ehealth) (571) JMIR Theme Issue: COVID-19 Special Issue (2458) Wearable Devices and Sensors (900) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1424) Infectious Diseases (non-STD/STI) (1588) mHealth for Health Administration (149) mHealth for Wellness, Behavior Change and Prevention (2912) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) mHealth in a Clinical Setting (621) Outbreak and Pandemic Preparedness and Management (1740) mHealth for Data Collection and Research (974) Occupational Health and Ergonomics/Prevention at the Workplace (241)

Published on in Vol 10, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29562, first published .
Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

Authors of this article:

Caroline A Clingan1 Author Orcid Image ;   Manasa Dittakavi1 Author Orcid Image ;   Michelle Rozwadowski1 Author Orcid Image ;   Kristen N Gilley1 Author Orcid Image ;   Christine R Cislo1 Author Orcid Image ;   Jenny Barabas2 Author Orcid Image ;   Erin Sandford2 Author Orcid Image ;   Mary Olesnavich2 Author Orcid Image ;   Christopher Flora2 Author Orcid Image ;   Jonathan Tyler1, 3 Author Orcid Image ;   Caleb Mayer3 Author Orcid Image ;   Emily Stoneman4 Author Orcid Image ;   Thomas Braun5 Author Orcid Image ;   Daniel B Forger3 Author Orcid Image ;   Muneesh Tewari2, 6, 7, 8 Author Orcid Image ;   Sung Won Choi1, 6 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

Journals

  1. Ojokoh B, Aribisala B, Sarumi O, Gabriel A, Omisore O, Taiwo A, Igbe T, Chukwuocha U, Yusuf T, Afolayan A, Babalola O, Adebayo T, Afolabi O. Contact Tracing Strategies for COVID-19 Prevention and Containment: A Scoping Review. Big Data and Cognitive Computing 2022;6(4):111 View
  2. Majeed A, Hwang S. Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments. Symmetry 2021;14(1):16 View
  3. Leite G, Albuquerque A, Pinheiro P. Applications of Technological Solutions in Primary Ways of Preventing Transmission of Respiratory Infectious Diseases—A Systematic Literature Review. International Journal of Environmental Research and Public Health 2021;18(20):10765 View
  4. Shausan A, Nazarathy Y, Dyda A. Emerging data inputs for infectious diseases surveillance and decision making. Frontiers in Digital Health 2023;5 View
  5. Song Z, Zhou S, Qin Y, Xia X, Sun Y, Han G, Shu T, Hu L, Zhang Q. Flexible and Wearable Biosensors for Monitoring Health Conditions. Biosensors 2023;13(6):630 View
  6. Magtibay K, Umapathy K. A Review of Tools and Methods for Detection, Analysis, and Prediction of Allostatic Load Due to Workplace Stress. IEEE Transactions on Affective Computing 2024;15(1):357 View
  7. Liu Y, Luo T, Ding C, Xuan L, Li J, Yang R. Progress in The Application of Flexible and Wearable Electrochemical Sensors in Monitoring Biomarkers of Athletes. Advanced Materials Technologies 2024;9(23) View