[Study of hybrid time-frequency method and characterization of atrial fibrillation from surface ECG]

With the non-invasive analysis of time-frequency features and instantaneous frequency (IFs) of atrial fibrillation (AF) from surface ECG signals, some important information reflecting the dynamic behavior of atria with AF can be extracted. In this paper is proposed a hybrid time-frequency analysis method, which uses the respective advantages of Gabor expansion and quadratic Wigner distribution. Our study showed that the time-frequency representation of atrial fibrillation signals was formulated into the combinations of time-frequency atoms series. By controlling the trade-off of resolution and interference terms via Manhattan distance threshold, this method in combination with moment-based computation obtained more robust estimation of IFs. The comparative analysis of 10 pairs of non-terminating and terminating types of AF signals suggested that hybrid estimation of IFs can detect the reduction of a majority of the fibrillatory rate when AF will end. Meanwhile, this method decreases compute burden and is a more robust way relative to peak-based or spectrogram method. So, the proposed method would have prospective applications in clinical management of atrial fibrillation.