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 [1-3]. Emotion recognition with machine learning based on EEG signals has been an exciting topic and employed in many areas such as health care, safe driving, and social security. In this paper, a review on EEG signal-based emotion recognition 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 emotions recognition process with various tools and technologies utilized in it [4]. Finally, it gives the issues and challenges for future research directions.