학술논문

Autocorrelation Function for Predicting Arrhythmic Recurrences in Patients Undergoing Persistent Atrial Fibrillation Ablation
Document Type
Conference
Source
2022 Computing in Cardiology (CinC) Computing in Cardiology (CinC), 2022. 498:1-4 Sep, 2022
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Electrodes
Atrial fibrillation
Rhythm
Feature extraction
Extraterrestrial measurements
Weaving
Orbits
Language
ISSN
2325-887X
Abstract
Persistent atrial fibrillation ablation has a high recurrence rate. In this work, we performed an analysis of bipolar intracavitary signals obtained with a conventional 24-pole diagnostic catheter (Woven Orbiter) placed in the right atrium and coronary sinus in a cohort of patients with persistent atrial fibrillation undergoing ablation to detect features predictive of acute procedural success (conversion to sinus rhythm during ablation) and the occurrence of recurrences. The goal is to arrive at a quantitative description of the degree of randomness of the atrial response in atrial fibrillation and to demonstrate the presence of hidden periodic components. This was done by the determination of the autocorrelation function. Results showed that higher correlation in relative maximum peaks, and a lower dominant atrial frequency (greater distance between relative amplitude maxima) may be associated with a greater likelihood of achieving reversion to sinus rhythm and lower probability of recurrences. A larger study is needed to draw conclusions.