A-EGM Features Extraction Using Wavelet Signal Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00193450" target="_blank" >RIV/68407700:21230/12:00193450 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

A-EGM Features Extraction Using Wavelet Signal Processing

Popis výsledku v původním jazyce

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 notwell 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 proce

Název v anglickém jazyce

A-EGM Features Extraction Using Wavelet Signal Processing

Popis výsledku anglicky

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 notwell 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 proce

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/GPP103%2F11%2FP106" target="_blank" >GPP103/11/P106: Integrace digitálního zpracování obrazu a metod umělé inteligence pro hodnocení komplexity intrakardiálních signálů</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IFMBE Proceedings: World Congress on Medical Physics and Biomedical Engineering

ISBN

978-3-642-29304-7

ISSN

1680-0737

e-ISSN

—

Počet stran výsledku

4

Strana od-do

534-537

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Beijing ( Peking)

Datum konání akce

26. 5. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—