A PERFORMANCE COMPARISON AND IMPROVEMENT FOR REMOVAL OF OCULAR ARTIFACTS IN EEG-BCI

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. It is an important testing method which enables the capture of very useful information relating to the different physiological states of the brain. . Unfortunately, EEG signals are highly contaminated with various artifacts, one of the artifacts that occur due to the eye-blinks and movement of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA).The main objective of the project is to reduce or eliminate ocular artifacts without damaging that part of the signal which is related to brain activity. It is used to develop an efficient and effective method to remove ocular artifacts using two method. First method is Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC) and second method by using LMS algorithm.comparison result can be shown Then the result can be simulated in Lab VIEW. I. INTRODUCTION The study of human brain function can benefit both engineering and medicine. Clinical neural monitoring is critical in diagnosing and treating many neurological disorders such as epilepsy. Brain-computer interfaces (BCIs) present the possibility of creating a direct link between humans and their environment, allowing the use of brain- controlled devices to assist people with disabilities. One problem in neural signal processing is the presence of noise and artifacts in neural recordings. Major artifacts can come from a variety of sources, including eye movement, muscle movement, cardiac rhythm, outside sources, and even neural processes other than the one of interest. Artifacts produced by eye movement and blinks, which are commonly referred to as ocular artifacts (OA).