Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00177120" target="_blank" >RIV/68407700:21230/10:00177120 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Evaluation of Atrial Fibrillation in Human Using Artificial Intelligence Methods
Original language description
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.
Czech name
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Czech description
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
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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Number of pages
3
Pages from-to
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Publisher name
Austrian Society for Cybernetics Studies
Place of publication
Vienna
Event location
Vienna
Event date
Apr 6, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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