BRAIN - COMPUTER INTERFACE FOR COMMUNICATION AND ESTIMATION OF HUMAN EMOTION FROM EEG AND VIDEO

The brain-computer interface (BCI) aim to use Electroencephalography (EEG) or other measures of brain functions can be implemented for communication with smart devices for disabled persons. For connection with different smart devices was used recorded with experimental setup electrophysiological signals for execution of five different mental tasks. The recorded brain signals were processed for their transformation into commands to different devices. This signal processing aims to extract some specific features of brain signals and transform them into algorithms for connection with smart devices. Processed signals after noise filtering, clustering and classification with Bayesian Network classifier and pair-wise classifier was estimated and put into brain-computer interface for connection with smart devices. Recent advances in emotion recognition use a combination of two intrapersonal modalities face and EEG to estimate emotion. In this research is made an attempt to combine received results on the base of record electrophysiological signals at execution of five different mental tasks with estimation of human emotion. This will help to provide a framework for reliable EEG emotional state estimation combined with facial emotion analysis in developed task-oriented BCI.