Extracting ERP by combination of Subspace Method and Lift Wavelet Transform

Event related potentials (ERP) recorded from the scalp include various noises. The main source of the noise is the spontaneous brain activity and it is called the background electroencephalography (EEG). Because EEG is highly colored, we wouldn´t effectively remove EEG noise by wavelet transform. This paper proposed a new approach that combined the subspace method and lift wavelet transform in order to reduce the number of trials required for the extraction of the brain event related potentials. First, the signal subspace is estimated by applying the singular value decomposition (SVD). Orthonormal projecting the raw data onto the estimated signal subspace can obtain a pre-denoised signal and it whitened the colored noise. Next, the ERPs are extracted by lift wavelet construction of the enhanced version. Simulation results show that the combination of both two methods provides much better capability than each of them separately