The removal of baseline drift is a difficult and important point in ECG preprocessing. This article discusses several commonly used methods to suppress ECG baseline drift:median filtering, high-pass filtering, curve fitting, wavelet transform, ECG-based feature points and morphological filtering methods. Under the circumstances of the baseline drift serious or weak, several methods for data are analyzed and compared. This article compares several commonly used methods as well as evaluation of application effects to provide a reference for the selection of baseline drift removal methods for ECG signals.
Keywords: ECG; baseline drift; filtering.