A Novel DWT Method for ECG Noise Elimination

An electrocardiogram (ECG) often contains various types of noises and artifacts that might lead to wrong analysis. Recently, many techniques based on discrete wavelet transform (DWT) for ECG noise elimination have been proposed. Determination of the number of decomposition levels, which could vary with the sampling rate (frequency sampling), is one of the main issues in DWT. This letter presents an automatic index, called mean power frequency (MPF) and is independent of the sampling rate, for stopping decomposing process when it achieves the optimum number of decomposition levels. The effectiveness of this scheme is expressed by the signal-to-noise ratio (SNR), mean square error (MSE), and correlation coefficient (CC) between the pure and corrected ECG. The results indicate that the applied method can remove Gaussian noise efficiently. (c) 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.