Subband Adaptive Shrinkage Function Using Fuzzy Logic

Abstract

ECG is the electrical activity of the heart which uses for the various diagnostic purposes. Denoising is a process which helps to remove the noise from the original signal. Wavelet transform is suitable for non stationary signal such as ECG signal, EEG signal, PPG signal etc. The wavelet coefficients obtained by wavelet transform are made zero which in turns reduces the noise to zero level. Fuzzy logic is a structured, powerful problem solving technique that approximates a function through linguistic variables. A fuzzy membership function is an abstract which each point in the input variable is mapped to a membership value between 0 and 1.In this paper, noise is removed from an ECG signal by using subband adaptive shrinkage function using the fuzzy logic. The threshold value is selected by the fuzzy membership function for signal denoising. Among the other shrinkages functions, subband adaptive method is preferred as it produces good result by holding linearity at discontinuities. The parameters used for measuring the performance are signal to noise ratio (SNR), percentage root mean square difference (PRD), and mean square error (MSE).