Emotional State Recognition with EEG Signals Using Subject Independent Approach

EEG signals vary from human to human and hence it is very difficult to create a subject independent emotion recognition system. Even though subject dependent methodologies could achieve good emotion recognition accuracy, the subject-independent approaches are still in infancy. EEG is reliable than facial expression or speech signal to recognize emotions, since it can not be fake. In this paper, a Multilayer Perceptron neural network based subject-independent emotion recognition system is proposed. Performance evaluation of the proposed system, on the benchmark DEAP dataset shows good accuracy compared to the state of the art subject independent methods.