0370 Clinical Validation of Cardiac Rhythm Monitoring Using a Wearable Dry-Electrode Home Sleep Test Device

Abstract Introduction Wearable, low–form-factor neurophysiologic sensors are reshaping sleep medicine by enabling high-fidelity home-based monitoring that more closely reflects natural sleep behavior, improving comfort, expanding accessibility, and reducing system-level costs. Their broad clinical adoption, however, requires rigorous evidence that wearable platforms can deliver measurements equivalent to gold-standard wired, gel-electrode systems. Recent studies have shown that dry-electrode wearables can faithfully capture key neurophysiologic features, including sleep staging, spindle detection and morphology, and REM Sleep Without Atonia (RSWA) scoring. Yet one essential domain remains critically underexplored: the fidelity of cardiac rhythm acquisition, particularly in patients with underlying cardiac disease. Here, we address this gap by directly comparing cardiac rhythm acquisition between a wearable dry-electrode sleep system and a conventional wired, gel-electrode platform in a cohort of cardiac patients. Methods We conducted a prospective comparison of cardiac rhythm monitoring using an FDA-cleared wearable system (X-trodes System M) and a gold-standard wired platform (Biopac). Consecutive adult patients were enrolled through the cardiology clinic at Sheba Medical Center, Israel. The wearable system uses ultrathin printed dry-electrode arrays embedded in small wireless adhesive patches to record EEG, ECG, EOG, and EMG. The platform is modular, supports optional respiratory sensors, and enables multi-night and multi-subject recordings. Results Seven patients were enrolled (median age 78). Cardiac histories included aortic stenosis (n=2), mitral regurgitation (n=1), ischemic heart disease (n=3), and Wolff–Parkinson–White (n=1). Conduction abnormalities included LBBB (n=1), RBBB (n=1), WPW (n=1), and first-degree AV block (n=1). One patient had atrial fibrillation. A total of 1,349 beats were available for RR analysis and 1,168 for PR, the discrepancy due to an AF episode. RR intervals showed < 1 ms mean error, SD ±2.8 ms, and MAE 1.5 ms. PR intervals showed 1.8 ms mean error, SD ±9.1 ms, and MAE 4.6 ms. Conclusion This study demonstrates that wearable dry-electrode technology can achieve RR and PR interval measurements equivalent to gold-standard wired systems, supporting its feasibility for cardiac rhythm monitoring during home sleep testing. These findings extend emerging evidence that next-generation home sleep platforms can deliver clinically reliable electrophysiologic data in complex cardiac populations. Support (if any)