Improved Emotion Identification with Novel Feature Extraction Technique Utilizing EEG Data

Abstract

In the recent era of technology, Automatic emotion detection has become a versatile tool due to the significance application of emotions recognisition. With the increasing popularity of human-computer interface applications, this study focuses on the identification of emotions using electro-encephalography (EEG) signals. The proposed approach offers a method to recognize the basic emotions using advance machine learning method. The aim of this research is to build an intelligent strategy that uses discrete signal processing for improving the accuracy of emotion identification by employing Support Vector Machines (SVM). The results show that the accuracy of proposed approach was found 98.23% for identifying the four different emotions like happiness, sad, current, and hate.