A Novel Preprocessing Tool to Enhance ECG R-wave Extraction
Various approaches have been proposed to detect the R-waves in the ECG. From the derivative-based to more complicated wavelet transform methods, the main goal of these approaches is to extract the R-waves from the perturbations present in the ECG. Our study aims at proposing a simple preprocessing tool that suppresses perturbations and enhances the R-waves in the ECG. Using sliding windows, short- and long-term signal energies are calculated for each sample in the ECG. A coefficient signal is then created as the ratio between the corresponding short- and long-term energies. The enhanced ECG is then calculated by multiplying the coefficient signal and the original ECG. The MIT-BIH database was used for evaluation and the proposed method was tested against synthetic white and EMG noises. Using the proposed method as a preprocessing tool to the classic Pan-Tompkins approach lead to a significant decrease over the number of false positive and false negative QRS complexes, when synthetic noise is added to ECG.