Dominant atrial fibrillatory frequency estimation using an extended Kalman smoother

In patients with atrial fibrillation (AF), the dominant repetition rate of the atrial fibrillatory waves (f-waves), or fibrillatory frequency (FF), (usually in the range 3-12 Hz) plays an important role for non-invasive assessment of atrial electrical remodeling. It is usually assessed from the electrocardiogram (ECG) by signal processing tools such as power spectral analysis and short-time Fourier transform (STFT), after ventricular activity (VA) cancellation. FF can also be estimated simultaneously with VA detection using an extended Kalman smoother (EKS), as recently proposed by us. In this paper, we try to simplify the model and adapt it to situations in which less computational power is available and only short signals are considered (e.g., mobile or E-health applications). In the proposed model, the ventricular activity (VA) is represented by a sum of Gaussian kernels, while a single sinusoidal function with constant frequency is employed for the atrial activity (AA). The strategy was validated using 290 synthetic signals obtained from ECGs in sinus rhythm (Physionet PTBDB), where P-waves were replaced by artificial f-waves, at different signal-to-noise (SNR) ratios. At a SNR of 0, 20 and 40 dB, the average root mean square errors were 0.22, 0.08 and 0.01 Hz respectively.