Abstract: The electroencephalogram (EEG) popularly known as brain waves represents the electrical activity of the brain. The scalp EEG is an average of the signals generated by various activities of many small zones of the cortical surface beneath the electrodes. An EEG is used to detect problems in the electrical activity of the brain. The pattern of electrical activity is useful for diagnosing a number of conditions that affect the brain. The conditions may be epilepsy, dementia, brain tumor etc. By analyzing the EEG signal we can also compare and differentiate the signals generated by brain for different emotions like happy, sad, anger etc. Recently, numerous research and techniques have been developed for processing, feature extraction and analysis of EEG signals. All these techniques and algorithms have their advantages and limitations. This proposed paper discusses various techniques and transformations proposed earlier in literature for processing and analysis of EEG signals in order to develop more effective and efficient algorithm.

Keywords: EEG, brain waves, feature extraction, analysis.