Electrocardiogram (ECG) denoising method utilizing Empirical Mode Decomposition (EMD) with SWT and a Mean based filter

Abstract

Electrocardiogram is an pivotal physiological signal that is exploited for the detection of cardiological ailments. An ECG signal necessarily gets polluted with different types of unwanted noise during its acquisition phase thereby deteriorating its quality. This imposes a constraint on its utility in disease diagnosis. It thus becomes necessary to remove these artifacts while at the same time preserving the main features of the signal. EMD based methods have been extensively used for the purpose. In this paper, we utilized a blended method that explores the denoising capability of EMD along with that of SWT and NLM filtering techniques to filter out 50 Hz sinusoidal AC noise and white noise. The efficiency of the presented method has been demonstrated in respect of the empirical parameters like SNR improvement and mean of square error values whilst using various records from the arrhythmia database of the MIT Beth Israel Hospital. The excellence of the method presented has been exhibited through comparison of the obtained results with an existing method