De-noising of EEG signals using Bayes Shrink based on Coiflet Transform

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 using threshold called Bayes Shrink based on Coiflet Transform.