Price Nicholas F, Berenfeld Omer, Devabhaktuni Vijay, Deo Makarand
Department of Electrical and Computer Engineering, University of Toledo, Toledo, OH 43607 USA.
Center for Arrhythmia Research, University of Michigan, Ann Arbor, MI 48107 USA.
Annu Model Simul Conf ANNSIM. 2022 Jul;2022:294-304. doi: 10.23919/annsim55834.2022.9859334. Epub 2022 Aug 23.
With the increased prevalence of atrial fibrillation (AF) - a rhythm disturbance in heart's top chambers - there is growing interest in accurate non-invasive diagnosis of atrial activity to improve its therapy. A key component in non-invasive analysis of atrial activity is a successful removal of the ventricular QRST complexes from electrocardiograms (ECGs). In this study, we have developed a new approach for an objective and physiologically-based evaluation of QRST cancellation methods based on comparisons with the power spectra of the AF. Three commonly used QRST cancellation methods were evaluated; namely, average beat subtraction, singular value cancellation, and principal component analysis. These methods were evaluated in time and frequency domains using a set of synthesized ECGs preserving the atrial-specific temporal and spectral properties. It was observed that the ABS method provided the best estimation when QRST morphological variability is low, while PCA produces an overall best estimate when a large QRST morphological variability is present.
随着心房颤动(AF)——心脏上部腔室的一种节律紊乱——患病率的增加,人们对准确无创诊断心房活动以改善其治疗的兴趣日益浓厚。心房活动无创分析的一个关键组成部分是成功地从心电图(ECG)中去除心室QRST复合波。在本研究中,我们基于与房颤功率谱的比较,开发了一种新的方法,用于对QRST消除方法进行客观且基于生理学的评估。评估了三种常用的QRST消除方法;即平均搏动减法、奇异值消除和主成分分析。使用一组保留心房特定时间和频谱特性的合成心电图,在时域和频域对这些方法进行了评估。观察到,当QRST形态变异性较低时,ABS方法提供了最佳估计,而当存在较大的QRST形态变异性时,PCA总体上产生了最佳估计。