Human emotion recognition using frequency & statistical measures of EEG signal

The purpose of the research is to evaluate the different human emotions through Electroencephalogram (EEG) signal and to receive information about the internal changes of brain state. The paper presents the detection of human emotion based on some salient features of EEG signal. For this purpose, seven emotional states have been specified such as relax, thought, memory related, motor action, pleasant, fear, and enjoying music. Several EEG signals have been collected for these states and analyzed using frequency transform and statistical measures. Different significant features have been extracted from the analyzed signal. Among various statistical measures skewness and kurtosis are chosen which indicate the largest dispersion in different mental states and help to evaluate different human emotions. Frequency analysis shows how the ranges of magnitude vary with different frequency components. On the basis of magnitude ranges different emotional states are identified. EEG signal provides an effective way in the functioning of the brain to study of mental behavior.