Time-frequency analysis compensating missing data for Atrial Fibrillation ECG assessment

Abstract

We propose a novel algorithm for temporal tracking of the fibrillatory frequency for Atrial Fibrillation (AF) ECG. Both Atrial activity extraction and fibrillatory frequency tracking are combined into a single algorithm and analytical expressions are derived for final time-frequency distributions, thus the proposed method is computationally efficient. It can also serve the general purpose of time-frequency analysis of a non-stationary signal with missing or corrupted data segments. The method uses short-time expansion of an orthogonal basis set, and regularized least squares solution used to compute a stable coefficients for the basis. A simplified and computationally efficient time-frequency distribution is derived based only on the coefficient vector. The algorithm is successfully applied to simulated as well as real ECG with AF, and its advantages over conventional average beat subtraction method are discussed.