Various Techniques for Denoising EEG signal : A Review (International Journal of Engineering and Computer Science, 2014)
The Electroencephalogram (EEG) signal is a biological non-stationary signal which contains important information about various activities of Brain. Analysis of EEG signals is useful for diagnosis of many neurological diseases such as epilepsy, tumors, and various problems associated with trauma. EEG measured by placing electrodes on scalp usually has very small amplitude , so the analysis of EEG signal and the extraction of information from this signal is a difficult problem. EEG signal become more complicated  to analyze by the introduction of artifacts such as line noise, eye blinks, eye movements, heartbeat, breathing, and other muscle activities. Proper diagnosis of disease requires faultless analysis of the EEG signals. The problem of denoising is quite varied due to variety of signals and noise. Discrete wavelet transform provides effective solution  for denoising non-stationary signals such as EEG due to its shrinkage property.