Automated Analysis of Emotion Recognition and Personality Prediction using EEG Signals

Abstract

Both human behaviour analysis and affective computing have been highly significant to the study of human-computer interaction (HCI). As a predictor of human behaviour, Psychologists and human resources workers have long utilised newlineemotion recognition and personality profiling. The study of human emotions and newlinepersonalities in order to design computer models that understand how people newlinerespond to various situations is essential for applications in many different areas, newlineincluding entertainment, health care, military, retail, and education. However in newlineliterature different methods are used to analyze emotions and personality traits newlinebut they suffer from data reliability issue and masking of physical behavior. The newlinelong and tedious process of identifying and estimating personalities is more of newlinea hindrance than a help. Therefore, in order to fulfill this requirement, there newlinemust be efforts made to overcome these problems and automate the process of newlinedetermining the presence of emotions and personality characteristics based on newlinetrustworthy data. A new approach is developed in this thesis for recognizing newlineemotions and predicting Myers Briggs Type Indicator based personality traits newlineusing brain signals called as electroencephalogram (EEG) signals. newline