EEG Denoising using SURE thresholding based on Wavelet Transforms

Abstract

The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. However, the presence of artifacts like electro-oculogram (EOG), Electrocardiogram (ECG), electromyogram (EMG) and power-line noise in the EEG signal is a major problem in the study of brain potentials. Hence, these superfluous signals are needed to be removed. There are various methods for removal of artifacts. This paper discusses a wavelet-based approach for correcting the artifacts generated by eye blinks, eyeball movements and facial muscle movements in EEG.