An iterative method of Ensemble Empirical Mode Decomposition for enhanced ECG signal denoising

ECG signals get contaminated frequently with noises such as power line interferences, baseline wander noise and muscle artifacts etc. For effective ECG signal denoising various filtering techniques are used to improve signal to noise ratio (SNR). In this paper a novel noise filtering algorithm based on iterative method of Ensemble Empirical mode decomposition (EEMD) has been used for ECG signal denoising and compared with other methods like EMD and wavelet thresholding. EEMD is applied to decompose the signal whose intrinsic mode functions (IMFs) are the mean of an ensemble of trials, each one of which consists of the signal plus a white noise of finite amplitude. For the analysis of the proposed method, the system is tested for ECG signal using MIT-BIH database. Our results showed that efficient noise reduction is the major advantage of using iterative EEMD filter for improving ECG quality, over the other methods tested.