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Impact of the pre-processing on the estimation of atria depolarization and repolarization on electrical and optical signals

Grant number: 23/04120-2
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): May 01, 2023
Effective date (End): April 30, 2024
Field of knowledge:Engineering - Biomedical Engineering - Bioengineering
Principal Investigator:João Loures Salinet Júnior
Grantee:Bruno Henrique Taglieri
Host Institution: Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas (CECS). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
Associated research grant:18/25606-2 - Accurate mapping of cardiac fibrillation activity: an experimental contribution, AP.JP


Atrial fibrillation (AF) is the most frequent sustained cardiac arrhythmia in clinical practice, affecting between 1 and 2% of the world's population. During AF, the interpretation of the signals and maps available through commercial electrical mapping systems in many cases is complex, hindering the correct characterization and location of arrhythmogenic sources, reducing the effectiveness of ablation treatment. The objective of this project is to analyze the influence of pre-processing techniques on the estimation of depolarization and electrical repolarization during sinus rhythm, electrical stimulation and AF on the electrograms of electrical and optical mapping. In this project, signs of the electrical activity of the epicardium to be obtained during experiments will be made available. The analyses will be performed by comparing the depolarization and repolarization times calculated from the epicardium signals obtained by the electrical and optical mappings simultaneously in the same locality of the atria. The comparison of each metric will be performed by the Person correlation coefficient. After the comparison between the metrics, the electrograms of the electrical mapping of the epicardium will be processed by different pre-processing techniques in order to improve the correlations. The analysis of the signals and generation of the maps will be carried out using the software Matlab Version 9.7 (R2019) (Mathworks, Inc.) or Python. This will allow quantifying the influence of traditional techniques used in pre-processing for the calculation of these important metrics used in electrophysiological studies of AF.

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