Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment

ABSTRACT/BACKGROUND

Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist‐worn devices for AF detection using photoplethysmography‐based algorithms perform only periodic checks when the user is stationary and are US Food and Drug Administration cleared for prediagnostic uses without intended use for clinical decision‐making. There is an unmet need for medical‐grade diagnostic wrist‐worn devices that provide long‐term, continuous AF monitoring.