Wavelet Transform-Based ECG Baseline Drift Removal for Body Surface Potential Mapping.

This paper gives a new approach for the removal of slow baseline drift components of electrocardiographic (ECG) signals based on the discrete wavelet transform. The baseline drift is efficiently removed by zeroing the scaling coefficients of the discrete wavelet transform. Such approach can easily be combined with other wavelet based approaches for random noise reduction or power line interference reduction. The new pre-processing approach can remove the low-frequency components without introducing distortions in the ECG waveform.