Literature DB >> 24111069

Decomposing atrial activity signal by combining ICA and WABS.

Huhe Dai, Ali Hassan Sodhro, Ye Li.   

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.

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Year:  2013        PMID: 24111069     DOI: 10.1109/EMBC.2013.6610882

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  F-Wave Extraction from Single-Lead Electrocardiogram Signals with Atrial Fibrillation by Utilizing an Optimized Resonance-Based Signal Decomposition Method.

Authors:  Junjiang Zhu; Jintao Lv; Dongdong Kong
Journal:  Entropy (Basel)       Date:  2022-06-10       Impact factor: 2.738

2.  Towards Cognitive Authentication for Smart Healthcare Applications.

Authors:  Ali Hassan Sodhro; Charlotte Sennersten; Awais Ahmad
Journal:  Sensors (Basel)       Date:  2022-03-09       Impact factor: 3.576

  2 in total

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