About: A-EGM Features Extraction Using Wavelet Signal Processing

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	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 A-EGM complexity description can be on the firm base and fully reproducible while evaluating RFA signals for AF treatment. 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 A-EGM complexity description can be on the firm base and fully reproducible while evaluating RFA signals for AF treatment. (en)
Title	A-EGM Features Extraction Using Wavelet Signal Processing A-EGM Features Extraction Using Wavelet Signal Processing (en)
skos:prefLabel	A-EGM Features Extraction Using Wavelet Signal Processing A-EGM Features Extraction Using Wavelet Signal Processing (en)
skos:notation	RIV/68407700:21230/12:00193450!RIV13-MSM-21230___
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(GPP103/11/P106), Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Křemen, Václav
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	121235
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/12:00193450
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Atrial Fibrillation; Intracardial Signals; Complex Fractionated Atrial Electrograms; Feature Extraction; Signal Processing (en)
http://linked.open.../riv/klicoveSlovo	Complex Fractionated Atrial Electrograms Feature Extraction Atrial Fibrillation Intracardial Signals Signal Processing
http://linked.open...ontrolniKodProRIV	[E4A07BE78DB8]
http://linked.open...v/mistoKonaniAkce	Beijing ( Peking)
http://linked.open...i/riv/mistoVydani	Heidelberg
http://linked.open...i/riv/nazevZdroje	IFMBE Proceedings: World Congress on Medical Physics and Biomedical Engineering
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Integration of digital signal processing and artificial intelligence methods for intracardial signal complexity evaluation
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Křemen, Václav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2012-05-26 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Transdisciplinární výzkum v oblasti biomedicínského inženýrství II
issn	1680-0737
number of pages	4 (xsd:int)
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-29304-7
http://localhost/t...ganizacniJednotka	21230

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