Fuzzy decision tree to classify complex fractionated atrial electrograms

Biomedizinische Technik. Biomedical Engineering
Christopher SchillingArmin Luik

Abstract

Catheter ablation has emerged as an effective treatment strategy for atrial fibrillation (AF) in recent years. During AF, complex fractionated atrial electrograms (CFAE) can be recorded and are known to be a potential target for ablation. Automatic algorithms have been developed to simplify CFAE detection, but they are often based on a single descriptor or a set of descriptors in combination with sharp decision classifiers. However, these methods do not reflect the progressive transition between CFAE classes. The aim of this study was to develop an automatic classification algorithm, which combines the information of a complete set of descriptors and allows for progressive and transparent decisions. We designed a method to automatically analyze CFAE based on a set of descriptors representing various aspects, such as shape, amplitude and temporal characteristics. A fuzzy decision tree (FDT) was trained and evaluated on 429 predefined electrograms. CFAE were classified into four subgroups with a correct rate of 81±3%. Electrograms with continuous activity were detected with a correct rate of 100%. In addition, a percentage of certainty is given for each electrogram to enable a comprehensive and transparent decision. The proposed ...Continue Reading

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Citations

Jan 18, 2016·Computer Methods and Programs in Biomedicine·Tobias Georg OesterleinArmin Luik
Jul 12, 2018·IEEE Transactions on Bio-medical Engineering·Tobias G OesterleinOlaf Dossel
Oct 10, 2015·Physiological Measurement·A Orozco-DuqueJ Bustamante
Apr 28, 2016·Biomedical Engineering Online·Andres Orozco-DuqueGerman Castellanos-Dominguez
Aug 16, 2021·European Heart Journal·Venkat D NagarajanSabine Ernst

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Software Mentioned

Coiflet
HistKurt
FDTx
FracSig
Ensite NavX
CART

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