Why the study?
AF diagnosis is often hindered by its frequently asymptomatic or paroxysmal nature, leading to a significant diagnostic gap in traditional monitoring.
Do wearable technologies utilizing photoplethysmography and mobile ECG improve atrial fibrillation screening compared to traditional monitoring?
Do wearable technologies utilizing photoplethysmography and mobile ECG improve atrial fibrillation screening compared to traditional monitoring?
Wearable technologies offer a promising approach for population-based atrial fibrillation screening, but require integration with physician judgment and face implementation challenges.
Background: Atrial fibrillation (AF) is a major public health challenge and a primary independent risk factor for ischemic stroke. The diagnosis of AF is often hindered by its frequently asymptomatic or paroxysmal nature, which leads to a significant diagnostic gap in traditional monitoring. Purpose: This review evaluates the clinical reliability of wearable technologies for AF screening and analyzes their impact on modern cardiovascular prevention and healthcare systems. Methods: A comprehensive literature search was conducted across major medical databases, focusing on landmark clinical trials, meta-analyses, and the latest European Society of Cardiology guidelines. Results: Contemporary wearable devices utilizing photoplethysmography and mobile ECG have demonstrated high positive predictive values for AF detection in large-scale studies such as the Apple Heart Study and Fitbit Heart Study. Advanced artificial intelligence algorithms further enhance diagnostic precision by reducing motion artifacts. However, successful clinical integration remains limited by socio-ethical challenges, including the digital divide and data privacy concerns. Conclusion: Wearable technologies represent a breakthrough in population-based screening, yet their clinical efficacy depends on a hybrid care model that integrates digital data with physician judgment.
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Sergejuk et al. (2026) studied this question.
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