Feature Extraction and Classification of EEG Signals Using Neural Network Based Techniques

EEG stands for Electroencephalogram. EEG is used to record signals from brain; signals are recorded from the scalp or cortex of brain. EEG used for both clinically purpose as well as for scientifically purpose. Hence measurement of EEG signals plays an important role in mind/brain studies. Reorganization of EEG signals from brain is one of the most overriding approaches to extract the data/knowledge from mind/brain dynamics. Analyzing Electrical activity of brain through EEG provide medical science to examine different brain diseases. Electrical activity of brain can easily be classified as normal brain waves or abnormal brain waves. Normal brain waves used to study various states of mind where as abnormal brain waves used to indicate medical problems. Classification of EEG signals play important role in medical science, some important applications for EEG wave classification are diagnosis of sleep disorders and construction of BCI to assist disabled person. Reorganization of EEG signals from brain is one of the most overriding approaches to extract the data/knowledge from mind/brain dynamics. Analyzing Electrical activity of brain through EEG provide medical science to examine different brain diseases.