A Wavelet-Based Method for Non-Invasive Dominant Frequency Detection in Atrial Fibrillation

摘要

Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good spatial correlation with those obtained with the non-invasive body surface potential mapping (BSPM). In this study, a robust BSPM-DF calculation method based on wavelet analysis is proposed. Continuous wavelet transform (Gaussian mother wavelet) along 40 scales in the pseudo-frequency range of 3-30 Hz is performed in each BSPM signal. DFs are estimated from the intervals between the peaks, representing the activation times, in the maximum energy scale. The results are compared with the traditionally widely applied Welch periodogram. The accuracy of both methods was assessed using the absolute errors between BSPM and atrial highest DFs (HDFs) and assumed correct if ≤ 1. The robustness of the methods was tested on different protocols: increasing levels of WGN, artificial DF harmonics presence, and reduction of the number of leads. 11 AF simulations and 12 AF patients are considered in the analysis. The proposed method outperformed the Welch approach, obtaining more correct estimations of atrial HDFs non-invasively in models (81.82% vs 45.45%) and patients (75.00% vs 66.67%) and being more robust to noise and reduction in spatial resolution, thus helping to increase the non-invasive diagnostic ability of BSPM in AF.