Role of Wearable Devices in Early Detection of Cardiac Arrhythmias

Cardiac arrhythmias, including atrial fibrillation (AF), ventricular tachycardia (VT), and bradycardia, contribute significantly to global cardiovascular morbidity and mortality, with AF affecting 2–4% of adults and increasing stroke risk by 5-fold. Early detection is critical to prevent complications such as stroke, heart failure, and sudden cardiac death. Wearable devices, leveraging photoplethysmography (PPG), single-lead electrocardiography (ECG), and machine learning algorithms, have emerged as transformative tools for real-time, non-invasive arrhythmia monitoring. This review synthesizes evidence from systematic searches of PubMed, Scopus, and Web of Science (2015–2025) using keywords such as “wearable devices,” “cardiac arrhythmias,” “atrial fibrillation detection,” and “ECG monitoring.” PPG and single-lead ECG achieve 85–95% sensitivity and specificity for AF detection, identifying subclinical arrhythmias in 20–30% of high-risk populations. Wearables facilitate timely interventions, such as anticoagulation for AF, reducing stroke risk by 30–40%. However, challenges like motion artifacts, data privacy, regulatory gaps, and clinical integration persist. This review highlights the potential of wearables to revolutionize arrhythmia management, emphasizing need for standardized validation, advanced algorithms, regulatory frameworks, and integration into healthcare systems.