Abstract
Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study aims to evaluate the sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.
Highlights
Atrial fibrillation (AF) is the most common arrhythmia with rising incidence and prevalence [1,2]; the current prevalence is estimated to be between 2% to 4% [3]
Our study suggests that reliable detection of AF in high-risk patients for AF is possible with the medical wearable used, during time periods with physical activity
Detection of AF with normalized root mean square of successive differences (nRMSSD) in five-minute periods showed higher sensitivity, but lower specificity than in other studies conducted with an active measurement approach; our results were obtained in a not physically restricted population [11,13]
Summary
Atrial fibrillation (AF) is the most common arrhythmia with rising incidence and prevalence [1,2]; the current prevalence is estimated to be between 2% to 4% [3]. AF is more common in males and shows an increasing prevalence with age [4]. AF is associated with a broad spectrum of clinical events, including ischemic stroke. The proportion of time in AF associated with a significant risk for complications is unknown, requiring further evaluation [6]. ECG Holter monitoring has limitations: Carrying an ECG Holter limits patients in their daily activities and restricts monitoring to relatively short periods of time. ECG Holters are prone to movement artifacts, and not reliable during phases of physical activity [8]
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