Efficient extraction of event related potentials by the combination of subspace method and wavelet transform

Abstract

This paper proposed a new approach in order to reduce the number of trials required for the extraction of the brain event related potentials (ERPs). The approach is developed by combining both the subspace methods and wavelet transform. The first step is to estimate the signal subspace by applying the singular value decomposition (SVD) and orthonormally projecting the raw data onto the estimated signal subspace to obtain an enhanced version. At the same time it whitened the colored noise. Next, the ERPs are extracted by wavelet denoising from the enhanced version. Simulation results show that combination of both two methods provides much better capability than each of them separately. The results of experiments showed that the practical processed results were effective.