A-EGM Features Extraction Using Wavelet Signal Processing
Though atrial electrogram (A-EGM) signal processing plays more and more important role in research that helps physicians to ease and shorten radiofrequency ablation (RFA) procedure of atrial fibrillation (AF),feature extraction algorithms are still not well and clearly understood and described in contemporary literature.Conversely different methods of A-EGM evaluation are compared and published frequently,but often based on these feature extraction algorithms that are not so well published.This paper is aimed to start to put the light on the basics that precedes using of features for A-EGM evaluation.Basic wavelet signal processing tools are used to preprocess and extract simple but (as proven in published research) valuable features of A-EGM signal that was measured during RFA of AF.This approach was proven and it helps to classify complexity of A-EGM signals.More detailed view on the extraction process is given here to enable an easy and reproducible usage of these A-EGM processing and feature extraction algorithms so that future research of AEGM complexity description can be on the firm base and fully reproducible while evaluating RFA signals for AF treatment.
Atrial fibrillation intracardial signals complex fractionated atrial electrograms feature extraction signal processing
V. Kremen
Department of Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
国际会议
World Congress on Medical Physics and Biomedical Engineering (2012年医学物理及生物医学工程国际会议(IFMBE))
北京
英文
534-537
2012-05-26（万方平台首次上网日期，不代表论文的发表时间）