Title :
Decomposing atrial activity signal by combining ICA and WABS
Author :
Huhe Dai ; Sodhro, Ali Hassan ; Ye Li
Author_Institution :
Key Lab. for Health Inf., Shenzhen Inst. of Adv. Technol., Shenzhen, China
Abstract :
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.
Keywords :
electrocardiography; independent component analysis; medical signal processing; AA signal extraction; BSS algorithms; ICA; WABS; atrial activity signal decomposition; atrial fibrillation; electrocardiogram; independent component analysis; multilead AA signal decomposition; multiple stable sources; statistical methods; surface ECG; weighted average beat subtraction; Atrial fibrillation; Classification algorithms; Electrocardiography; Feature extraction; Matrix decomposition; Source separation; Surface waves;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6610882