Wavelet Domain Nonlinear Filtering for Evoked Potential Signal Enhancement

Abstract

A wavelet domain nonlinear filtering method for improving the signal-to-noise ratio (SNR) of the evoked potentials (EP) is proposed. The method modifies the selective filtering technique proposed for edge detection in images by Xu et al. for the case of signals which require a smooth transition at the edge points. It identifies the significant features of a noisy signal based on the correlation between the scales of its nonorthogonal subband decompositions. The signal transition information from interscale correlation coupled with the change in variance around the identified transition region is used to differentiate between noise and the signal. A nonlinear function such as a Gaussian smoothing function applied around the identified edge in the wavelet domain leads to smoothing in the signal space also. Numerical results obtained by applying the proposed nonlinear filtering method on middle latency responses of auditory evoked potentials show that the method is well suited for signal enhancement applications.