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Electroencephalogram is the method of recording the electrical activity of the brain via sensors (electrodes) placed on the surface of the scalp. EEGs, which are of the order of microvolt, have greater potential for the diagnosis and treatment of mental and brain diseases and abnormalities. However, EEG signals are subject to various kinds of contaminants (i.e) artifacts which arise from human beings themselves.EEG recordings are often significantly distorted by Eye blinks and eye ball movements which cause changes to the electrical fields around the eye. These interpretations, which are often termed as noises, are however problematic. These are of the order of millivolts. The frequency range of EEG waves is 0-64Hz while artifacts occur within the range of 0-16Hz. Therefore, it becomes a must for the removal of ocular artifacts from the EEG signals. The wavelet based EOG algorithm, when applied to the entire length of the EEG signals, results in thresholding both high frequency and low frequency components, including the non-ocular artifacts zones, but it produces considerable loss in the valuable background EEG activity. The ocular artifacts can be detected by means of visual inspection. But, the EOG correction procedure requires ocular artifacts time zones to be fed as input , which is indeed a tedious process .This necessitates the need for the automatic detection of ocular artifacts zones. In this paper, we have proposed a method for automatically identifying the slow varying artifacts zones, followed by the application of wavelet based adaptive thresholding algorithm to the identified artifacts zones. This preserves the background EEG information. Adaptive thresholding is applied only to the artifacts zones. This method preserves both the low frequency components and the shape of the EEG signal in the non-artifact zones, which is very important in clinical diagnosis. In this paper, we have proposed a thresholding method using Haar Wavelet Transform for the removal of artifacts from the recorded EEG signal.

A Certain Exploration on EEG Signal for the Removal of Artefacts using Power Spectral Density Analysis through Haar wavelet Transform