Automated System for EEG’s Artifacts Removal using Adaptive Filter

Author

C.Vimal,P.Krishan,B.Sathish,S.Vineeth,D.Chakravathy.

B.E. (BIOMEDICAL ENGG)

P.S.G.COLLEGE OF TECHNOLOGY.COIMBATORE-04.

Guided by E.MALAR, P.S.G.COLLEGE OF TECHNOLOGY.

Abstract

Extracting required electrical signal corresponds to brain activity from an Electroencephalogram is a major problem in Neuroscience. The sensed cerebral signals have several origins that lead to the complexity of their identification. Therefore, the noise removal is of the prime necessity to make easier data interpretation and representation and to recover the signal that matches perfectly a brain functioning. A common problem faced during the clinical recording of the EEG signal, are the interference signals generated by different organs. For example, eye-blinks, the movement of the eye balls produce Ocular artifacts that interferes the brain signals. It has been

known for quite some time now that the Alpha rhythm of the EEG, which is the principal resting rhythm of the brain in adults while they are awake, is directly influenced by visual stimuli. Auditory and mental arithmetic tasks with the eyes closed leads to strong alpha waves, which are suppressed when the eyes are opened.

A number of methods of dealing with ocular artifact in the EEG, focusing on the relative merits of a variety of EOG correction procedures have been performed. A cascade of three adaptive filters based on a Least Mean Squares (LMS) algorithm to reduce the common artifacts present in EEG signals without removing significant information embedded in these records is most common in nowadays. We proposed an approach using one adaptive filter instead of a cascade of three adaptive filters and the ocular artifacts are removed very easily. The suppression ratio in our approach is high. We conclude that adaptive cancellation is an efficient processing technique for improving the quality of EEG signals in biomedical analysis.