A Brief Overview on Analysis and Feature Extraction of Electroencephalogram Signals

Abstract

Human brain cells are active even during sleep and communicate through electrical impulses. Electroencephalogram (EEG) signals can be used to extract the correct information from the hu-man brain and classify it with different mental functions. Non-inventiveness, high temporal reso-lution, and relatively low financial cost are the reasons for the use of EEG widely in medical en-gineering research. Extraction of a feature is very important and fundamental for EEG signal classification. In this paper, some of the methods used to extract the features from EEG signals are reviewed. In biomedical research, the classification of EEG signals plays an important role. According to the principles of pattern recognition, the classification process has two stages: fea-ture extraction and classification. This study explains the EEG signal classification. Features are extracted for different bands.