A Study on Relationship between Personal Feature of EEG and Human's Characteristic for BCI Based on Mental State

This paper discusses the relationship the result classified the electroencephalogram (EEG) patterns while listening to music and the human's nature, which indicates the personal feature of a human, based on the egogram pattern. The EEC analysis calculates the power spectra of the frequency of the EEC signal, divides into the frequency bands based on theta, alpha, and beta rhythms, and evaluates whether the music matches mood of the user or not through EEC pattern classification. A k-nearest neighbor classifier is used to classify the EEC patterns. The egogram is used for detecting nature of the human. Finally, we discuss the relationship the result of EEC pattern classification and the human's nature. An interesting finding was that the recognition accuracy of the EEC pattern meaning the response of them on negative stimuli became high when the subject was classified into the egogram pattern with introverted nature.