Atrial activity extraction from single lead ECG recordings: Evaluation of two novel methods
Atrial activity extraction from single lead ECG recordings: Evaluation of two novel methods
复制标题
DOI：
10.1016/j.compbiomed.2012.12.005
复制
发表时间：
2013-03-01
影响因子：
7.7
通讯作者：
Li, Ye
中科院分区：
文献类型：
--
作者：
Dai, Huhe;Jiang, Shouda;Li, Ye
提出了两种不同的方法从房颤的单导联心电图（ECG）中提取心房活动（AA）信号。第一个是加权平均节拍减法（WABS）方法。用于构建 QRS 模板的 QRS 复合波系数是通过最小化均方误差获得的。第二种方法基于最大似然估计（MLE）。使用广义高斯模型估计 AA 信号和心室活动 (VA) 信号的概率密度函数。然后通过最大化似然函数提取AA信号。使用模拟信号和临床心电图来评估 ABS、WABS 和基于 MLE 的算法的性能。与 ABS 相比，基于 WABS 和 MLE 的算法分别将正态均方误差降低了 23.5% 和 20.2%。 (C) 2012 Elsevier Ltd. 保留所有权利。
Two different methods for extracting atrial activity (AA) signal from single lead electrocardiogram (ECG) of atrial fibrillation were proposed. The first one is a weighted average beat subtraction (WABS) method. Coefficients of QRS complexes used for constructing QRS template were obtained by minimizing mean square error. The second method is based on maximum likelihood estimation (MLE). Probability density functions of AA signal and ventricular activity (VA) signals were estimated using generalized Gaussian model. Then AA signal was extracted by maximizing likelihood function. Simulated signal and clinical ECG were used to evaluate the performance of ABS, WABS and MLE-based algorithm. In comparison with ABS, WABS and MLE-based algorithm reduced normal mean square error by 23.5% and 20.2%, respectively. (C) 2012 Elsevier Ltd. All rights reserved.