A Review on Emotion Recognition with Machine Learning Using EEG Signals

Abstract

Emotions are critical in people's daily lives since their decision making, interaction, intelligence, and perception are all influenced by the emotions they display. Emotion recognition with machine learning based on EEG signals has been an exciting topic and employed in several areas, such as health care, social security, and safe driving. In this paper, a review on emotion recognition using EEG signals employing machine learning is carried out based on various factors, such as the stimulus used, equipment, modalities, filters, features, classifiers, and detected emotions, along with the limitations. This paper identifies the basic methodology used in the emotion recognition process with various tools and technologies utilized in it. Finally, it gives the issues and challenges for future research directions.