Review on Emotion Recognition Based on Electroencephalography

Haoran Liu; Ying Zhang; Yujun Li; Xiangyi Kong

doi:10.3389/fncom.2021.758212

Review on Emotion Recognition Based on Electroencephalography

Front Comput Neurosci. 2021 Oct 1:15:758212. doi: 10.3389/fncom.2021.758212. eCollection 2021.

Authors

Haoran Liu¹, Ying Zhang², Yujun Li¹, Xiangyi Kong¹

Affiliations

¹ The Boiler and Pressure Vessel Safety Inspection Institute of Henan Province, Zhengzhou, China.
² Patent Examination Cooperation (Henan) Center of the Patent Office, CNIPA, Zhengzhou, China.

Abstract

Emotions are closely related to human behavior, family, and society. Changes in emotions can cause differences in electroencephalography (EEG) signals, which show different emotional states and are not easy to disguise. EEG-based emotion recognition has been widely used in human-computer interaction, medical diagnosis, military, and other fields. In this paper, we describe the common steps of an emotion recognition algorithm based on EEG from data acquisition, preprocessing, feature extraction, feature selection to classifier. Then, we review the existing EEG-based emotional recognition methods, as well as assess their classification effect. This paper will help researchers quickly understand the basic theory of emotion recognition and provide references for the future development of EEG. Moreover, emotion is an important representation of safety psychology.

Keywords: DEAP; DREAMER; EEG; SEED; convolution neural network; emotion recognition.

Publication types

Review