Application of portable electroencephalograph device in controlling and identifying emotion

Nowadays, communication between the computer and human is based on different methods such as using signals: gesture, voice, bio-signals. One of the special methods that always interesting in scientists is Brain Computer Communication Interface (BCI). In this study, we focused on communication capabilities of computers and humans through Electroencephalograph signal (EEG). Equipment used in the study is some EPOC versions of Emotiv. The study consisted of 2 parts: the first part, we focus on the analysis and identification of EEG signal in real time to develop control applications. The identification method includes: selecting the threshold of amplitude, signal spectrum analyzer. The raw signal that we obtained in real time will be continuously filtered to remove noise and transfer input data packets for identification blocks. Some basic results that our group has achieved in control: go forward, go backward, turn left, turn right (4 channels controller). The second part, we analyzed brain waves to emotional identification of the user. Our method is based on emotion recognition model of Russell. The value of two axes in the plane is determined by the algorithm parameters Higuchi through HFD index. The package of emotion recognition has achieved some positive results when identifying the emotions: fear, frustration, sadness, joy, excitement and satisfaction in real time. Through the process research, combining emotion and identification of controls will be helpful, minimize ability to influence feelings of control signals are not really wanted. The study will be further developed in building package extended functionality and complete automation training algorithm for compatibility with many different users who use the device.