A Ventricular Far-field Artefact Filtering Technique for Atrial Electrograms

Abstract

Intracardiac atrial electrograms (EGM) are prone to ventricular far-field potentials due to ventricular depolarization. In this study, a filtering technique integrating independent component analysis (ICA) and wavelet decomposition has been proposed to significantly reduce the ventricular far-field contents while preserving the EGM morphology related to atrial activations. First, the wavelet decomposition is applied to each unipolar EGM. Then, ICA is applied to the decomposed unipolar EGM components and surface ECG template. Each independent component is cross-correlated with the simultaneously recorded ECG template and the three components with higher correlation coefficients were eliminated before applying inverse ICA. Total of 126 unipolar EGM collected from an atrial fibrillation patient have been included. Results indicate that the proposed filtering can reduce the ventricular signal power by around 17 dB (decibel). Furthermore, the signal-tonoise ratio is increased by approximately 17 dB after applying the proposed filtering. In conclusion, the proposed filtering method could be used for atrial fibrillation-related intracardiac mapping for catheter ablation. Further studies on a larger dataset are essential to quantify the exact impact of ventricular artefacts on both unipolar and bipolar EGM and the effectiveness of the proposed filtering technique.

Far-field Intracardiac Electrograms Removal Enables Highly Reliable Automatic Cycle Length Estimation During Atrial Arrhythmias

“…Previous works use source separation methods [1][2][3], template matching and subtraction [4], as well as adaptive ventricular cancellation [5] on either bipolar or unipolar electrograms with multiple leads or only one lead. Inspired by [4], we implemented a new approach trying to leverage wavelet decomposition and different methods to combine and produce a blueprint to be subtracted.…”