학술논문

Singular Spectrum Analysis of Atrial Activations to Predict Atrial Fibrillation Recurrence after Ablation Procedure
Document Type
Conference
Source
2018 Computing in Cardiology Conference (CinC) Computing in Cardiology Conference (CinC), 2018. 45:1-4 Sep, 2018
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Matrix decomposition
Veins
Lung
Time series analysis
Spectral analysis
Rhythm
Language
ISSN
2325-887X
Abstract
The goal of pulmonary vein ablation for atrial fibrillation (AF) is returning to normal sinus rhythm; nevertheless it success is limited in part by uncertainly in the mechanisms that sustain AF. 43 AF patients were submitted to an ablation procedure and monitored after ablation. Dominant frequency from intra-atrial recordings obtained before the intervention were analysed in order to predict AF recurrence. The novelty of this study is that dominant frequency was calculated from reconstructed signal by singular spectrum analysis (SSA) application. Patients that maintained sinus rhythm and patients with recurrence in AF showed differences in left atrium dominant frequencies, with higher values in the recurrent AF group than in group without recurrence in the arrhythmia (p=0.02). Moreover, differences between both atria were found in the non-recurrent group, with 5.76 ± 1.31 Hz in the left atrium vs. 6.25±1.23 Hz in the right atrium (p=0.03). These findings show the potential of SSA as a preprocessing method and results are congruent with previous studies.