Fully automatic screening for atrial fibrillation using a photoplethysmography based wristband and a novel smart infrastructure

Abstract

Abstract Background Atrial Fibrillation (AF) is the leading cause of stroke, and its prevalence is expected to rise. While early detection is crucial in preventing thromboembolic events, its often asymptomatic and paroxysmal nature makes it challenging to capture using conventional electrocardiography (ECG). Photoplethysmography (PPG) enabled devices, such as smartwatches, allow continuous monitoring of the heart rhythm and accurate screening for AF. Purpose In this study, we aimed to build an IT-infrastructure for fully automated screening of AF in hospitalised patients at risk using a PPG-based wrist worn wearable device. Methods We conducted an investigator-initiated, prospective, clinical trial to evaluate the performance of a PPG-based wristband coupled to an automatic data process device hub in hospitalised patients. Participants with a CHA2DS2-VASc score of two or higher and no prior history of AF were eligible for the study. Consenting participants received a wristband with a built-in PPG sensor to be worn during the entire hospital stay. Data from the wristband was automatically transmitted, stored, analysed and visualised. When absolute arrhythmia (AA) was detected in the PPG signal, a subsequent seven-day Holter ECG was performed to confirm the diagnosis. Results A total of 346 patients were included in the analysis (age 72 ± 10 years; 175 females (50.6%); mean CHA2DS2-VASc score of 3.5 ± 1.3). No data was lost in the process. The mean monitoring time was 4.3 ± 4.4 days, 45.9% was evaluable. In twelve patients (3.5%, CI: 1.5% - 5.4%) absolute arrhythmia (AA) was detected in the PPG-signal. The mean screening time until first detection of AA was 14.7 ± 16.8 hours. The highest detection rate was observed within the first 24 hours of screening (p = 0.004) (Figure 1). The AA burden per hour was 1.9 times greater during the night (22:00 - 06:00) compared to the day (p = 0.003) (Figure 2). Of the 346 patients, 304 (87.9%) were compliant in wearing the wristband for the entire hospitalisation. In nine patients a Holter ECG was recorded, no AF was identified. Conclusions We successfully established an infrastructure for automated AF screening in hospitalised patients using wrist-worn PPG devices, enabling real-time visualisation of incoming data and facilitating therapeutic interventions with minimal delay. To our knowledge this is the first hospital to implement a fully automated AF screening infrastructure based on PPG devices. In a population at risk, AA was identified in 3.5% of all patients. The high compliance rate of the wearable device further supports its feasibility and utility in clinical practice.Figure 1:Time to first detection of AAFigure 2:Total AA burden per hour