Atrial fibrillation (AF) is often asymptomatic and paroxysmal. Screening and monitoring are
needed especially for people at high risk. This study sought to use camera-based remote …

Background: Wearable devices have evolved as screening tools for atrial fibrillation (AF). A
photoplethysmographic (PPG) AF detection algorithm was developed and applied to a …

Background Continuous photoplethysmography (PPG) monitoring with a wearable device
may aid the early detection of atrial fibrillation (AF). Objective We aimed to evaluate the …

Objective: We propose a non-contact approach for atrial fibrillation (AF) detection from face
videos. Methods: Face videos, electrocardiography (ECG), and contact …

Video-based Photoplethysmography (VPPG) can identify arrhythmic pulses during atrial
fibrillation (AF) from facial videos, providing a convenient and cost-effective way to screen for …

Objective To evaluate the diagnostic performance of a deep learning system for automated
detection of atrial fibrillation (AF) in photoplethysmographic (PPG) pulse waveforms …

Background Atrial fibrillation (AF), a common cause of stroke, often is asymptomatic.
Smartphones and smartwatches can detect AF using heart rate patterns inferred using …

Background Current wearable devices enable the detection of atrial fibrillation (AF), but a
machine learning (ML)–based approach may facilitate accurate prediction of AF onset …

Background It is estimated that 33.5 million people in the world have developed atrial
fibrillation (AF), and an estimated 30% of patients with AF are unaware of their diagnosis …

Background Early self-detection of atrial fibrillation (AF) can help delay and/or prevent
significant associated complications, including embolic stroke and heart failure. We …