Chu Justin, Yang Wen-Tse, Chang Yao-Ting, Yang Fu-Liang
Research Center for Applied Sciences, Academia Sinica, 128 Academia Rd., Sec. 2, Nankang, Taipei City 115-29, Taiwan.
Department of Biomechatronics Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei City 10607, Taiwan.
Diagnostics (Basel). 2022 May 24;12(6):1304. doi: 10.3390/diagnostics12061304.
Atrial fibrillation (AFib) is a common type of arrhythmia that is often clinically asymptomatic, which increases the risk of stroke significantly but can be prevented with anticoagulation. The photoplethysmogram (PPG) has recently attracted a lot of attention as a surrogate for electrocardiography (ECG) on atrial fibrillation (AFib) detection, with its out-of-hospital usability for rapid screening or long-term monitoring. Previous studies on AFib detection via PPG signals have achieved good results, but were short of intuitive criteria like ECG p-wave absence or not, especially while using interval randomness to detect AFib suffering from conjunction with premature contractions (PAC/PVC). In this study, we newly developed a PPG flux (pulse amplitude) and interval plots-based methodology, simply comprising an irregularity index threshold of 20 and regression error threshold of 0.06 for the precise automatic detection of AFib. The proposed method with automated detection on AFib shows a combined sensitivity, specificity, accuracy, and precision of 1, 0.995, 0.995, and 0.952 across the 460 samples. Furthermore, the flux-interval plot configuration also acts as a very intuitive tool for visual reassessment to confirm the automatic detection of AFib by its distinctive plot pattern compared to other cardiac rhythms. The study demonstrated that exclusive 2 false-positive cases could be corrected after the reassessment. With the methodology's background theory well established, the detection process automated and visualized, and the PPG sensors already extensively used, this technology is very user-friendly and convincing for promoted to in-house AFib diagnostics.
心房颤动(AFib)是一种常见的心律失常类型,临床上通常无症状,这会显著增加中风风险,但可通过抗凝治疗预防。作为心电图(ECG)检测心房颤动(AFib)的替代方法,光电容积脉搏波描记图(PPG)最近备受关注,因其可在院外用于快速筛查或长期监测。以往关于通过PPG信号检测AFib的研究取得了良好结果,但缺乏像ECG P波是否缺失这样直观的标准,尤其是在利用间期随机性检测合并早搏(PAC/PVC)的AFib时。在本研究中,我们新开发了一种基于PPG通量(脉搏幅度)和间期图的方法,只需设置不规则指数阈值20和回归误差阈值0.06,即可精确自动检测AFib。所提出的AFib自动检测方法在460个样本中显示出的综合灵敏度、特异性、准确性和精确性分别为1、0.995、0.995和0.952。此外,通量-间期图配置还可作为一种非常直观的工具用于视觉重新评估,通过其与其他心律不同的独特图形模式来确认AFib的自动检测。该研究表明,重新评估后可纠正仅有的2例假阳性病例。随着该方法的背景理论得到充分确立、检测过程自动化且可视化,以及PPG传感器已被广泛使用,这项技术非常便于用户使用且令人信服,可推广用于院内AFib诊断。