Development of an Algorithm for Human Emotional State Correction via Electroencephalographic Signal Processing

The present paper is aimed at developing and investigating an original algorithm for human emotional state correction using complex processing and analysis of electroencephalographic signals (EES). EES parameters have been measured in a relaxed state, in natural activity, and in six modes of audio-visual stimulation (AVS): Sleep, Learn, Energ, Create, Fun, and Special. The conducted research has evidenced cerebral hemisphere arousal in subjects (with eyes open in natural activity and in the Energ mode), which explicitly illustrates the emotional state. Emotional stability has been recorded in the Sleep and Fun modes.