Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study - Hirten, Robert P; Danieletto, Matteo; Tomalin, Lewis; Choi, Katie Hyewon; Zweig, Micol; Golden, Eddye; Kaur, Sparshdeep; Helmus, Drew; Biello, Anthony; Pyzik, Renata; Charney, Alexander; Miotto, Riccardo; et al. (Journal of medical Internet research, 2021)
Keywords: Adult; Asymptomatic; Autonomic nervous system; Between-subjects design; Central nervous system; Chemical analysis; Circadian rhythm; Circadian Rhythm - physiology; Coronaviruses; COVID-19; COVID-19 - diagnosis; COVID-19 - physiopathology; COVID-19 - virology; COVID-19 Testing - methods; Diagnostic tests; Disease transmission; Female; Health care; Health Personnel; Heart rate; Heart Rate - physiology; Humans; Hypothesis testing; Infections; Male; Medical diagnosis; Medical personnel; Multimedia; Nervous system; Observational studies; Original Paper; Physiology; Predictions; Questionnaires; SARS-CoV-2 - genetics; SARS-CoV-2 - isolation & purification; Severe acute respiratory syndrome coronavirus 2; Smartphones; Symptoms; Wearable computers; Wearable Electronic Devices; Workers; app; observational; wearable; data; diagnosis; COVID-19; wearable device; symptom; identification; heart rate variability; infectious disease; prediction; physiological