Assessment of the relational strength between triggers detected in physiological signals and the occurrence of atrial fibrillation episodes.

Abstract

Despite the growing interest in understanding the role of triggers in paroxysmal atrial fibrillation (AF), solutions beyond questionnaires to identify a broader range of triggers remain lacking. This study aims to investigate the relation between triggers detected in wearable-based physiological signals and the occurrence of AF episodes. Methods: Week-long physiological signals were collected during everyday activities from 35 patients with paroxysmal AF, employing an ECG patch attached to the chest and a photoplethysmogram (PPG)-based wrist-worn device. The signals acquired by the patch were used for detecting triggers of physical exertion, psychophysiological stress, lying on the left side, and sleep disturbances, as well as to annotate AF episodes. To assess the relation between detected triggers and the occurrence of AF episodes, a measure of relational strength is employed accounting for pre- and post-trigger AF burden. The utility of ECG- and PPG-based AF detectors in determining AF burden and assessing the relational strength is also analyzed. Results: Physical exertion emerged as the trigger associated with the largest increase in relational strength for the largest number of patients (p< 0.01). On the other hand, no significant difference was observed for psychophysiological stress and sleep disorders. When AF episodes are captured using AF detectors, the relational strength exhibits a moderate correlation with the relational strength of the annotated AF, withr= 0.66 for ECG-based AF detection andr= 0.62 for PPG-based AF detection. Conclusions: The findings indicate a patient-specific increase in relational strength for all four types of triggers. Significance: The proposed approach has the potential to facilitate the implementation of longitudinal studies and can serve as a less biased alternative to questionnaire-based AF trigger detection.