Detection of Common Respiratory Infections, Including COVID-19, Using Consumer Wearable Devices in Health Care Workers: Prospective Model Validation Study.

Background: The early detection of respiratory infections could improve responses against outbreaks. Wearable devices can provide insights into health and well-being using longitudinal physiological signals.

Objective: The purpose of this study was to prospectively evaluate the performance of a consumer wearable physiology-based respiratory infection detection algorithm in health care workers.

Detection of Atrial Fibrillation in a Large Population Using Wearable Devices: The Fitbit Heart Study.

Background: Morbidity from undiagnosed atrial fibrillation (AF) may be preventable with early detection. Many consumer wearables contain optical photoplethysmography (PPG) sensors to measure pulse rate. PPG-based software algorithms that detect irregular heart rhythms may identify undiagnosed AF in large populations using wearables, but minimizing false-positive detections is essential.

Rationale and design of a large population study to validate software for the assessment of atrial fibrillation from data acquired by a consumer tracker or smartwatch: The Fitbit heart study.

Background: Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment.

X-ray fused with MRI guidance of pre-selected transcatheter congenital heart disease interventions.

Objectives: To determine whether X-ray fused with MRI (XFM) is beneficial for select transcatheter congenital heart disease interventions.

Background: Complex transcatheter interventions often require three-dimensional (3D) soft tissue imaging guidance. Fusion imaging with live X-ray fluoroscopy can potentially improve and simplify procedures.