Automatic denoising of single-trial evoked potentials

We present an automatic denoising method based on the wavelet transform to obtain single trial evoked potentials. The method is based on the inter- and intra-scale variability of the wavelet coefficients and their deviations from baseline values. The performance of the method is tested with simulated event related potentials (ERPs) and with real visual and auditory ERPs. For the simulated data the presented method gives a significant improvement in the observation of single trial ERPs as well as in the estimation of their amplitudes and latencies, in comparison with a standard denoising technique (Donoho's thresholding) and in comparison with the noisy single trials. For the real data, the proposed method largely filters the spontaneous EEG activity, thus helping the identification of single trial visual and auditory ERPs. The proposed method provides a simple, automatic and fast tool that allows the study of single trial responses and their correlations with behavior.