Unbiased FIR denoising of ECG signals

Abstract

Applications of the unbiased finite impulse response (UFIR) estimation approach are discussed to improve measurements of the electrocardiography (ECG) signals. One of the standard methods providing denoising and extracting features of the ECG signals is based on the one-step prediction. We show that better accuracy is obtained by using the UFIR filter and the UFIR smoothing filter with adapted averaging horizon length. To investigate the trade-off between the predictive and UFIR filtering algorithms, we exploit the ECG measurements data for normal heart beating. Better performance of the designed UFIR denoising algorithms is demonstrated.