Artificial intelligence (AI) is increasingly used in electrocardiography (ECG) to assist in
diagnosis, stratification, and management. AI algorithms can help clinicians in the following …

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-
risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions …

Artificial intelligence (AI) can detect left ventricular systolic dysfunction (LVSD) from
electrocardiograms (ECGs). Wearable devices could allow for broad AI-based screening but …

The use of consumer wearable devices (CWDs) to track health and fitness has rapidly
expanded over recent years because of advances in technology. The general population …

The proliferation of physiological sensors opens new opportunities to explore interactions,
conduct experiments and evaluate the user experience with continuous monitoring of bodily …

Atrial fibrillation (AF) is the most common arrhythmia with a high burden of morbidity
including impaired quality of life and increased risk of thromboembolism. Early detection and …

Background Electrocardiograms (ECGs) are used by physicians to record, monitor, and
diagnose the electrical activity of the heart. Recent technological advances have allowed …

(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often
underdiagnosed, despite being present in 13–26% of ischemic stroke patients. Recently, a …

Availability of devices capable of continuous rhythm monitoring such as smartwatches,
implantable loop recorders, or pacemakers/defibrillators is continuously increasing …

Abstract Direct-to-consumer (D2C) wearables are becoming increasingly popular in
cardiovascular health management because of their affordability and capability to capture …