Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods

Popis výsledku v původním jazyce

Detection of Atrial fibrillation and identification of complex fractionated atrial electrograms (CFAEs) sites is important part of the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Signal processing algorithms are the key part of this task. Artificial intelligence (AI) algorithms 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 AI algorithms used here for signal processing, description and classification were developed and validated. AI algorithms used and tested here showed promising results of A-EGM classification of highly fractionated A-EGMs.

Název v anglickém jazyce

Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods

Popis výsledku anglicky

Detection of Atrial fibrillation and identification of complex fractionated atrial electrograms (CFAEs) sites is important part of the development of new AF ablation strategies. CFAE may represent the electrophysiological substrate for atrial fibrillation (AF). Signal processing algorithms are the key part of this task. Artificial intelligence (AI) algorithms 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 AI algorithms used here for signal processing, description and classification were developed and validated. AI algorithms used and tested here showed promising results of A-EGM classification of highly fractionated A-EGMs.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the Twentieth European Meeting on Cybernetics and Systems Research

ISBN

978-3-85206-178-8

ISSN

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e-ISSN

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Počet stran výsledku

3

Strana od-do

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Název nakladatele

Austrian Society for Cybernetics Studies

Místo vydání

Vienna

Místo konání akce

Vienna

Datum konání akce

6. 4. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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