Wavelet based eeg signal analysis on small abnormalities for emergency medication application
Pappu, Md. Habibullah
Tutul, Kabir Hossain
Firoj, Md. Mahim Bin
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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.