Internal medicine

Radiology

Sinus rhythm

Atrial fibrillation

Machine learning

Wearable computer

Cardiology

Embedded system

Atrial flutter

Normal Sinus Rhythm

Smartwatch

Computer science

Diagnostic accuracy

Medical diagnosis

Medicine

Frontiers in Cardiovascular Medicine

The diagnostic accuracy of proprietary smartwatch algorithms and the interpretability of smartwatch ECG tracings may differ between available models. We compared the diagnostic potential for detecting atrial fibrillation (AF) of three commercially available smartwatches.We performed a prospective, non-randomized, and adjudicator-blinded clinical study of 100 patients in AF and 100 patients in sinus rhythm, patients with atrial flutter were excluded. All patients underwent 4 ECG recordings: a conventional 12-lead ECG, Apple Watch Series 5®, Samsung Galaxy Watch Active 3®, and Withings Move ECG® in random order. All smartwatch ECGs were analyzed using their respective automated proprietary software and by clinical experts who also graded the quality of the tracings.The accuracy of automated AF diagnoses by Apple and Samsung outperformed that of Withings, which was attributable to a higher proportion of inconclusive ECGs with the latter (sensitivity/specificity: 87%/86% and 88%/81% vs. 78%/80%, respectively, p < 0.05). Expert interpretation was more accurate for Withings and Apple than for Samsung (sensitivity/specificity: 96%/86% and 94%/84% vs. 86%/76%, p < 0.05), driven by the high proportion of uninterpretable tracings with the latter (2 and 4% vs. 15%, p < 0.05).Diagnosing AF is possible using various smartwatch models. However, the diagnostic accuracy of their automated interpretations varies between models as does the quality of ECG tracings recorded for manual interpretation.

Smartwatch Electrocardiograms for Automated and Manual Diagnosis of Atrial Fibrillation: A Comparative Analysis of Three Models