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

• Main Authors: Hirten, Robert P (Author), Danieletto, Matteo (Author), Tomalin, Lewis (Author), Choi, Katie Hyewon (Author), Zweig, Micol (Author), Golden, Eddye (Author), Kaur, Sparshdeep (Author), Helmus, Drew (Author), Biello, Anthony (Author), Pyzik, Renata (Author), Charney, Alexander (Author), Miotto, Riccardo (Author), Glicksberg, Benjamin S (Author), Levin, Matthew (Author), Nabeel, Ismail (Author), Aberg, Judith (Author), Reich, David (Author), Charney, Dennis (Author), Bottinger, Erwin P (Author), Keefer, Laurie (Author), Suarez-Farinas, Mayte (Author), Nadkarni, Girish N (Author), Fayad, Zahi A (Author)
• Format: Book
• Published: JMIR Publications, 2021-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundChanges in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. ObjectiveWe performed an evaluation of HRV collected by a wearable device to identify and predict COVID-19 and...