This paper is in the following e-collection/theme issue:
New Methods (964) JMIR Theme Issue: COVID-19 Special Issue (2461) Infectious Diseases (non-STD/STI) (1594) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Wearable Devices and Sensors (905) Outbreak and Pandemic Preparedness and Management (1743) Fitness Trackers and Smart Pedometers/Accelerometers (571) Surveillance Systems (468) mHealth for Data Collection and Research (982)Published on in Vol 23, No 2 (2021): February
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/26107, first published
.
Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study
Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study
Authors of this article:
Robert P Hirten1, 2 ; Matteo Danieletto2, 3 ; Lewis Tomalin4 ; Katie Hyewon Choi4 ; Micol Zweig2, 3 ; Eddye Golden2, 3 ; Sparshdeep Kaur2 ; Drew Helmus1 ; Anthony Biello1 ; Renata Pyzik5 ; Alexander Charney3, 6, 7 ; Riccardo Miotto2, 3 ; Benjamin S Glicksberg2, 3 ; Matthew Levin8 ; Ismail Nabeel9 ; Judith Aberg10 ; David Reich8 ; Dennis Charney11, 12 ; Erwin P Bottinger2 ; Laurie Keefer1, 6 ; Mayte Suarez-Farinas3, 4 ; Girish N Nadkarni2, 13, 14 ; Zahi A Fayad5, 15