Evaluation of Endocardial Electrograms Fractionation Complexity in Human Using Statistical Pattern Recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00163372" target="_blank" >RIV/68407700:21230/09:00163372 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Evaluation of Endocardial Electrograms Fractionation Complexity in Human Using Statistical Pattern Recognition

Popis výsledku v původním jazyce

Identification of complex fractionated atrial electrograms (CFAEs) sites is crucial for the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Progress in signal processing algorithms is the key part of this task. Algorithm for automated description of atrial electrograms (A-EGMs) fractionation based on wavelet transform and several feature extraction methods and statistical pattern recognition was proposed and methodology of A-EGM processing was designed and tested. The algorithms for signal processing, description and classification were developed and validated using a representative set of 1:5 s A-EGMs (n = 113) ranked by 3 independent experts into 4 classes of fractionation: 1 - organized atrial activity; 2 - mild; 3 - intermediate; 4 - high degree of fractionation.

Název v anglickém jazyce

Evaluation of Endocardial Electrograms Fractionation Complexity in Human Using Statistical Pattern Recognition

Popis výsledku anglicky

Identification of complex fractionated atrial electrograms (CFAEs) sites is crucial for the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Progress in signal processing algorithms is the key part of this task. Algorithm for automated description of atrial electrograms (A-EGMs) fractionation based on wavelet transform and several feature extraction methods and statistical pattern recognition was proposed and methodology of A-EGM processing was designed and tested. The algorithms for signal processing, description and classification were developed and validated using a representative set of 1:5 s A-EGMs (n = 113) ranked by 3 independent experts into 4 classes of fractionation: 1 - organized atrial activity; 2 - mild; 3 - intermediate; 4 - high degree of fractionation.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany

ISBN

978-3-642-03897-6

ISSN

1680-0737

e-ISSN

—

Počet stran výsledku

3

Strana od-do

—

Název nakladatele

Springer Science+Business Media

Místo vydání

Berlin

Místo konání akce

Mnichov

Datum konání akce

7. 9. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—