Validation of an Algorithm for Continuous Monitoring of Atrial Fibrillation Using a Consumer Smartwatch.

Abstract Background Consumer devices with broad reach may be useful for screening for atrial fibrillation (AF) in appropriate populations. However, currently there are no consumer devices capable of continuous monitoring for AF. Objective To estimate the sensitivity and specificity of a smartwatch algorithm for continuous detection of AF from sinus rhythm in a free-living setting. Methods We studied a commercially available smartwatch with photoplethysmography (W-PPG) and electrocardiogram capabilities (W-ECG). We validated a novel W-PPG algorithm combined with a W-ECG algorithm in a free-living setting, comparing the results to a 28-day continuous ECG patch (P-ECG). Results A total of 204 participants completed the free-living study, recording 81,944 hours with both P-ECG and smartwatch measurements. We found a sensitivity of 87.8% (95% confidence interval: 83.6-91.0%) and a specificity of 97.4% (97.1-97.7%) for the W-PPG algorithm (every 5-minute classification), a sensitivity of 98.9% (98.1-99.4%) and a specificity of 99.3% (99.1-99.5%) of the W-ECG algorithm and a sensitivity of 96.9% (93.7%-98.5%) and a specificity of 99.3% (98.4-99.7%) for W-PPG triggered W-ECG with a single W-ECG required for confirmation of AF. We found a very strong correlation of W-PPG in quantifying AF Burden when compared to P-ECG (r = 0.98). Conclusions Our findings demonstrate that a novel algorithm using a commercially available smartwatch can continuously detect AF with excellent performance and that confirmation with a W-ECG further enhances specificity. Furthermore our W-PPG algorithm can estimate AF burden. Further research is needed to determine whether this is useful in screening for AF in select at-risk patients.