A Study on Enhancement Techniques For Electrocardiogram Signals

Electrocardiogram (ECG) is a noninvasive technique that is used as a diagnostic tool for cardiovascular diseases. During the acquisition and transmission of ECG signals, different noises get embedded with it such as channel noise, muscle artifacts, electrode motion and baseline wander. In this project two techniques for ECG enhancement is proposed. The first method is based on Empirical Mode Decomposition and second method is based on time-frequency domain filtering using S-Transform. The performance of both techniques is compared with commonly used Wavelet Transform (WT) ECG enhancement technique. In EMD based ECG enhancement technique, the noisy ECG signal is initially decomposed into a set of Intrinsic Mode Functions (IMFs). In this method, the IMFs which are dominated by noise are automatically determined using Spectral Flatness (SF) measure and then filtered using butterworth filters to remove noise. This method gives good performance with high SNR and lower RMSE for channel noise. However, the method fails to provide signal enhancement for other types of noises. In S-Transform based enhancement technique, noisy ECG signal is represented in time-frequency domain using S-Transform. Next, masking and filtering technique is applied to remove unwanted noise components from time-frequency domain. This method gives good performance with high SNR and lower RMSE for different noises that are more probable to get embedded with ECG signal during its acquisition and transmission.