Abstract:
The Electroencephalogram (EEG) is a very crucial and effective tool for brain monitoring system
as well as detection of various abnormalities on behalf of both regular checkup and in case of any
emergency. This project aims to show an improved and more effective way of monitoring the brain
and its disruptions. It also gives an enormous opportunity to analyze the brain signal more deeply
considering the different environments. The project is divided into two parts as the EEG data
reading and the signal processing. The EEG data reading part is responsible to extract the EEG
signal from the body and eradicate the high frequency components and power line noise. The
signal processing part can work to filter the signal to eliminate the background noise. As the current
analyzing technologies are not sufficient enough to deal with the sudden abnormalities or even
very small abnormalities, the proposed method provides an effective way of analyzing the data
more accurately. The system has been developed using the wavelet tool in MATLAB. Because of
the availability of statistical information of the EEG data, the system can detect the smallest
possible abnormalities even in the harsh conditions. Extracting various statistical parameters along
with the other processing techniques including filtering, the proposed method can monitor the
brain as well as detect any type of abnormalities in a more accurate and effective way.
