A method of removing baseline drift in ECG signal based on morphological filtering

Abstract

Removing baseline drift is an important step in preprocessing ECG signal. The traditional methods have disadvantages of large computation and poor results. This paper utilizes the morphology theory combined with the characteristics of ECG signal to propose a morphological method for removing the baseline drift, which uses different shapes and sizes to design a two-stage morphological filter and perform cascaded combination operations of closing-opening and opening-closing respectively. The proposed method is verified that it can maintain the morphological specificity, improve the SNR, reduce the MSE, and remove the noise efficiently.