QRST Cancellation based on the empirical mode decomposition

Baseline drift and QRST residues are frequently present after QRST cancellation. This study deals with the improvement of atrial signal quality after QRST cancellation using an empirical mode decomposition (EMD) based post-processing. The EMD decomposes non-stationary signals into narrow-band components, known as intrinsic mode functions (IMFs). Simulated and clinical 30-second segments of estimated atrial activity (after QRST cancellation) on lead VI were decomposed into IMFs using an EMD algorithm. The DF and the energy ratio between TQ and QRS segments for each enhanced IMF component were used to select the IMFs that correspond to atrial activity. The atrial activity signal was taken as the sum of the selected IMFs. The performance of the method is compared with that of a standard post-processing approach using an infinite impulse response bandpass filter.