Biomedical Engineering Institute, Kaunas University of Technology, Kaunas, Lithuania.
Physiol Meas. 2019 Feb 22;40(2):025003. doi: 10.1088/1361-6579/ab029c.
This study proposes an algorithm for the detection of atrial fibrillation (AF), designed to operate on extended photoplethysmographic (PPG) signals recorded using a wrist-worn device of own design.
Robustness against false alarms is achieved by means of signal quality assessment and different techniques for suppression of ectopic beats, bigeminy, and respiratory sinus arrhythmia. The decision logic is based on our previously proposed RR interval-based AF detector, but modified to account for differences between interbeat intervals in the ECG and the PPG. The detector is evaluated on simulated PPG signals as well as on clinical PPG signals recorded during cardiac rehabilitation after myocardial infarction.
Analysis of the clinical signals showed that 1.5 false alarms were on average produced per day with a sensitivity of 72.0% and a specificity of 99.7% when 89.2% of the database was available for analysis, whereas as many as 15 when the RR interval-based AF detector, boosted by accelerometer information for signal quality assessment, was used. However, a sensitivity of 97.2% and a specificity of 99.6% were achieved when increasing the demands on signal quality so that 50% was available for analysis.
The proposed detector offers promising performance and is particularly well-suited for implementation in low-power wearable devices, e.g. wrist-worn devices, with significance in mass screening applications.
本研究提出了一种心房颤动（AF）检测算法，旨在对使用自主设计的腕戴设备记录的扩展光电容积脉搏波（PPG）信号进行操作。
通过信号质量评估和抑制异位搏动、二联律和呼吸窦性心律失常的不同技术来实现抗假警报的稳健性。决策逻辑基于我们之前提出的基于 RR 间隔的 AF 检测器，但进行了修改以考虑 ECG 和 PPG 之间的间期差异。该检测器在模拟 PPG 信号以及心肌梗死后心脏康复期间记录的临床 PPG 信号上进行了评估。
对临床信号的分析表明，当分析数据库的 89.2%可用时，平均每天会产生 1.5 次假警报，敏感性为 72.0%，特异性为 99.7%，而当使用基于 RR 间隔的 AF 检测器并通过加速度计信息增强信号质量评估时，会产生多达 15 次假警报。然而，当提高信号质量要求，使 50%的信号可用时，敏感性达到 97.2%，特异性达到 99.6%。
所提出的检测器具有有前景的性能，特别适合于低功耗可穿戴设备（例如腕戴设备）的实现，在大规模筛查应用中具有重要意义。
