Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study.

Robert P Hirten Matteo Danieletto Lewis E Tomalin Katie Hyewon Choi Micol Zweig Eddye A Golden Sparshdeep Kaur Drew S Helmus Anthony Biello Renata Pyzik Alexander W Charney Riccardo Miotto Benjamin Scott Glicksberg Matthew A Levin Ismail Nabeel Judith A Aberg David L Reich Dennis S Charney Erwin P Böttinger Laurie Keefer Mayte Suárez-Fariñas Girish Nitin Nadkarni Zahi Adel Fayad

Published in: Journal of medical Internet research (2021)

Longitudinally collected HRV metrics from a commonly worn commercial wearable device (Apple Watch) can predict the diagnosis of COVID-19 and identify COVID-19-related symptoms. Prior to the diagnosis of COVID-19 by nasal swab polymerase chain reaction testing, significant changes in HRV were observed, demonstrating the predictive ability of this metric to identify COVID-19 infection.

Keyphrases

coronavirus disease
sars cov
respiratory syndrome coronavirus
heart rate
blood pressure
depressive symptoms
electronic health record
data analysis