Dai Huhe, Sodhro Ali Hassan, Li Ye
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5849-52. doi: 10.1109/EMBC.2013.6610882.
In this paper we proposed a novel technique for Atrial Activity (AA) decomposition in Electrocardiogram (ECG) of Atrial Fibrillation (AF). The main purpose of our proposed technique is to decompose AA signal by combining two statistical methods, Independent Component Analysis (ICA)-existing and Weighted Average Beat Subtraction (WABS)-new, for AF with multiple stable sources, respectively. We found the limits of BSS algorithms which are mostly used to extract AA signal, while beauty of our proposed algorithm is that it decomposes multi-lead AA signals from surface ECG with AF. Our proposed technique is verified with clinical data and the results demonstrate that our proposed method is feasible.
在本文中，我们提出了一种用于心房颤动（AF）心电图（ECG）中心房活动（AA）分解的新技术。我们提出的技术的主要目的是分别通过结合两种统计方法，即现有的独立成分分析（ICA）和新的加权平均搏动减法（WABS），来分解具有多个稳定源的AF的AA信号。我们发现了大多数用于提取AA信号的盲源分离（BSS）算法的局限性，而我们提出的算法的优点在于它能从伴有AF的体表心电图中分解多导联AA信号。我们提出的技术通过临床数据得到了验证，结果表明我们提出的方法是可行的。
