Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania.
Faculty of Electrical and Electronics Engineering, Kaunas University of Technology, Kaunas, Lithuania.
Physiol Meas. 2024 Sep 23;45(9). doi: 10.1088/1361-6579/ad79b3.
Despite the growing interest in understanding the role of triggers of 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.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 potential triggers due to physical exertion, psychophysiological stress, lying on the left side, and sleep disturbances. 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 usefulness of ECG- and PPG-based AF detectors in determining AF burden and assessing the relational strength is also analyzed.Physical exertion emerged as the trigger associated with the largest increase in relational strength for the largest number of patients ( < 0.01). On the other hand, no significant difference was observed for psychophysiological stress and sleep disorders. The relational strength of the detected AF exhibits a moderate correlation with the relational strength of annotated AF, with = 0.66 for ECG-based AF detection and = 0.62 for PPG-based AF detection.The findings indicate a patient-specific increase in relational strength for all four types of trigger.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.
尽管人们越来越关注理解阵发性心房颤动 (AF) 触发因素的作用，但除了识别更广泛范围的触发因素的问卷之外，仍然缺乏解决方案。本研究旨在调查可穿戴生理信号中检测到的触发因素与 AF 发作之间的关系。我们从 35 名阵发性 AF 患者在日常活动中采集了长达一周的生理信号，使用贴在胸部的心电图贴片和基于光电容积脉搏波 (PPG) 的腕戴设备。贴片采集的信号用于检测因体力活动、心理生理压力、左侧卧位和睡眠障碍引起的潜在触发因素。为了评估检测到的触发因素与 AF 发作之间的关系，采用了一种考虑到触发前后 AF 负担的关系强度度量来评估。还分析了 ECG 和 PPG 为基础的 AF 检测器在确定 AF 负担和评估关系强度方面的有用性。体力活动是与大多数患者（<0.01）AF 负担增加最大的相关触发因素。另一方面，心理生理压力和睡眠障碍没有观察到显著差异。检测到的 AF 的关系强度与注释的 AF 的关系强度具有中等相关性，基于 ECG 的 AF 检测的=0.66，基于 PPG 的 AF 检测的=0.62。研究结果表明，所有四种类型的触发因素都会导致患者特定的关系强度增加。该方法有可能促进纵向研究的实施，并可以作为基于问卷的 AF 触发检测的替代方法，具有更小的偏见。
