Biometric Based User Authentication Using EEG Signals

Electroencephalography (EEG) is measuring of brain electrical activity which recorded from the scalp by attaching voltage-sensitive electrodes. The brain activities continuously create positive and negative voltage potential which is modeled using as a series of rhythmic wave forms. It has been shown that EEG oscillatory patterns depends on the state of cognition and the dynamics of the brain activity are reflected in these waveform. In the recent years, published reports show that there is strong correlation between the EEG signals and its owner, which explains why the EEG has been proposed as a usable tool for user identification and authentication. EEG based authentication methods require the user to perform a particular mental task. Every part of the brain is responsible for either mental or physical activity. Based on the tasks that the user does, it has to be expected that the activity of the neurons in parts of the brain responsible for this task increases, and these activities will be shown in the electrodes attached to these parts. To perform the user authentication, a set of appropriate feature should be extracted from the EEG signals which is used by classification algorithms to classify each user. In this paper, the EGG based authentication methods and required processes are reviewed