Towards an EEG-based emotion recognizer for humanoid robots

In the field of interaction between humans and robots emotions have been disregarded for a long time. During the last few years interest in emotion research in this area has been constantly increasing as giving a robot the ability to react to the emotional state of the user can help to make the interaction more human-like and enhance the acceptance of the robots. In this paper we investigate a method to facilitate emotion recognition from electroencephalographic signals. For this purpose we developed a headband to measure electroencephalographic signals on the forehead. Using this headband we collected data from five subjects. To induce emotions we used 90 pictures from the International Affective Picture System (IAPS) belonging to the three categories pleasant, neutral, and unpleasant. For emotion recognition we developed a system based on support vector machines (SVMs). With this system an average recognition rate of 47.11% could be achieved on subject dependent recognition.