Comparison of Different Classifiers for Biometric System Based on EEG Signals

Characteristics in EEG signals related to the motor imagery can be used to build up a biometric system. However, for the practical implementation of a biometric system, the classifier plays a crucial role. In this paper, I compared the performance of three different classifiers for the detection of the imagined movements in a group of subjects on the basis of EEG signals. The classifiers compared here were those based on Linear Discrimination Analysis (LDA), Artificial Neural Network (ANN) and Support Virtual Machine (SVM). Results show a better performance of the LDA classifier with the respect to the other classifiers.