Abstract
AimsThe 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.MethodsWe 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.ResultsThe 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).ConclusionDiagnosing 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.
Highlights
Atrial fibrillation (AF) is the most common sustained arrhythmia in clinical practice but often remains undiagnosed
All smartwatch ECG recordings were saved as PDF documents for offline analysis, anonymized, randomized and each automatic diagnosis was removed before distribution to two blinded electrophysiologists who independently interpreted each tracing and assigned one of three possible diagnoses: AF, sinus rhythm (SR), or unclassified
Of the 100 patients in SR, 86 ECG recordings were correctly diagnosed as SR, 1 incorrectly as AF, and 13 were not classified (3 due to poor recording, 3 due to a heart rate of
Summary
Atrial fibrillation (AF) is the most common sustained arrhythmia in clinical practice but often remains undiagnosed. The process of recording an ECG, analyzing it to generate an automated diagnosis of AF, and providing options to transmit these results to the wearer’s physician(s) are similar between smartwatch manufacturers Their diagnostic algorithms are proprietary and not made available for analysis. The diagnostic accuracy of these algorithms and the ability of healthcare professionals to correctly interpret smartwatch-based ECGs may differ between commercially available smartwatches. Given this technology’s widespread and growing use, mass screening for AF using various smartwatch-based technologies may effectively soon occur, the results of which will require clinical decisions on the part of healthcare professionals. The primary objective of our study was to compare the diagnostic performance of smartwatch ECGs from three companies (Apple, Samsung, and Withings), their ability to accurately differentiate sinus rhythm (SR) from AF using either their automated algorithms or through review of recorded smartwatch ECG tracings
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