New biometric approach based on motor imagery EEG signals

A research on biometry based on motor imagery EEG signals was described. In this study, I select EEG signals related to motor imagery, and a model was built. Estimated model parameters as feature vector were extracted, and then to classified by an artificial neural network. Two different classify cases, including authentication and identification, were investigated. Four types of motor imagery EEG signals and three subjects were compared. Experiment results show that EEG carrying individual-specific information can be successfully exploited for purpose of person authentication and identification.