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Multivariate classification of atrial substrate during atrial fibrillation

Grant number: 19/05192-1
Support type:Scholarships in Brazil - Master
Effective date (Start): June 01, 2019
Effective date (End): May 31, 2021
Field of knowledge:Engineering - Biomedical Engineering - Medical Engineering
Principal Investigator:Takashi Yoneyama
Grantee:Arthur Santos Bezerra
Home Institution: Divisão de Engenharia Eletrônica (IEE). Instituto Tecnológico de Aeronáutica (ITA). Ministério da Defesa (Brasil). São José dos Campos , SP, Brazil

Abstract

Atrial Fibrillation (AF) is the most common sustained cardiac arrhythmia in the clinical practice and one of the main causes of cerebrovascular accident. It is known that the pulmonary veins (PVs) are involved in the beginning and maintenance of AF, and that the isolation of the PVs (PVI) through radiofrequency catether ablation is efficient in the treatment of paroxystic AF. However, the ablation treatment of persistent AF continues to be a challenge due to its complex physiopathology, culminating in an intense debate regarding new methods to guide ablation. Therefore, the development of more efficient methods for the correct identification of atrial tissue responsible for the perpetuation of the arrhythmia is crucial for the advancement of ablative treatment for persistent AF. The properties of the atrial tissues can be studies through attributes extracted from atrial electrograms (AEGs) collected during AF. Recent investigations considered only one characteristic of AEGs to represent atrial substrate, which can be insufficient to describe such a complex phenomenon as AF. As such, the proposed work will investigate, through different supervised and non-supervised classification models, the combination of multiple attributes extracted from AEGs collected from persistent AF patients to discern the mechanisms of maintenance and perpetuation of AF. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ALMEIDA, TIAGO P.; SORIANO, DIOGO C.; MASE, MICHELA; RAVELLI, FLAVIA; BEZERRA, ARTHUR S.; LI, XIN; CHU, GAVIN S.; SALINET, JOAO; STAFFORD, PETER J.; NG, G. ANDRE; SCHLINDWEIN, FERNANDO S.; YONEYAMA, TAKASHI. Unsupervised Classification of Atrial Electrograms for Electroanatomic Mapping of Human Persistent Atrial Fibrillation. IEEE Transactions on Biomedical Engineering, v. 68, n. 4, p. 1131-1141, APR 2021. Web of Science Citations: 1.

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