Artificial intelligence-enabled atrial fibrillation detection using smartwatches: current status and future perspectives

被引：7

作者：

Papalamprakopoulou, Zoi ^{[1
]}

Stavropoulos, Dimitrios ^{[2
]}

Moustakidis, Serafeim ^{[3
]}

Avgerinos, Dimitrios ^{[4
]}

Efremidis, Michael ^{[4
]}

Kampaktsis, Polydoros N. ^{[5
]}

机构：

[1] Univ Buffalo, Dept Med, Div Gastroenterol Hepatol & Nutr, Sch Med & Biomed Sci, Buffalo, NY USA

[2] Univ Pittsburgh, Sch Med, Dept Ophthalmol, Pittsburgh, PA USA

[3] AiDEAS, Tallinn, Estonia

[4] Onassis Cardiac Surg Ctr, Athens, Greece

[5] Aristotle Univ Thessaloniki, Dept Med, Med Sch, Thessaloniki, Greece

来源：

FRONTIERS IN CARDIOVASCULAR MEDICINE | 2024年 / 11卷

关键词：

atrial fibrillation; smartwatches; photoplethysmography; single-lead electrocardiography; artificial intelligence; machine learning; PHOTOPLETHYSMOGRAPHY; VALIDATION; DEVICES; TRIAL; SMART; WATCH;

D O I：

10.3389/fcvm.2024.1432876

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Atrial fibrillation (AF) significantly increases the risk of stroke and heart failure, but is frequently asymptomatic and intermittent; therefore, its timely diagnosis poses challenges. Early detection in selected patients may aid in stroke prevention and mitigate structural heart complications through prompt intervention. Smartwatches, coupled with powerful artificial intelligence (AI)-enabled algorithms, offer a promising tool for early detection due to their widespread use, easiness of use, and potential cost-effectiveness. Commercially available smartwatches have gained clearance from the FDA to detect AF and are becoming increasingly popular. Despite their promise, the evolving landscape of AI-enabled smartwatch-based AF detection raises questions about the clinical value of this technology. Following the ongoing digital transformation of healthcare, clinicians should familiarize themselves with how AI-enabled smartwatches function in AF detection and navigate their role in clinical settings to deliver optimal patient care. In this review, we provide a concise overview of the characteristics of AI-enabled smartwatch algorithms, their diagnostic performance, clinical value, limitations, and discuss future perspectives in AF diagnosis.

引用

页数：8

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