Baseline Wander Removal for ECG Signals Based on Improved EMD

Electrocardiogram (ECG) is the physical interpretation of the electrical conductivity of the heart resulting from the muscular activities. It provides an effective way to observe heart diseases during medical treatments and studies. During the acquisition and transmission of ECG signal in the medical environment, the signal is often corrupted by various types of noises. The transmission of ECG regularly introduces noise due to terrible channel conditions. Moreover, there are different types of noises inherent in the data collection process. In order to reduce the impact of noise, in this paper, we proposed an algorithm based on the EMD and the piecewise polynomial fitting to remove the baseline wander for ECG signals. Here, the effect of this algorithm on wandered ECG signals is discussed elaborately with graphical interpretations. It is also analyzed that why this algorithm works better to remove baseline wander by using EMD and combine the piecewise polynomial fitting to denoise the signal processed by the EMD.