EEG based Emotion Recognition: A Tutorial and Review

Abstract

Emotion recognition technology through analyzing the EEG signal is currently an essential concept in Artificial Intelligence and holds great potential in emotional health care, human-computer interaction, multimedia content recommendation, etc. Though there have been several works devoted to reviewing EEG-based emotion recognition, the content of these reviews needs to be updated. In addition, those works are either fragmented in content or only focus on specific techniques adopted in this area but neglect the holistic perspective of the entire technical routes. Hence, in this paper, we review from the perspective of researchers who try to take the first step on this topic. We review the recent representative works in the EEG-based emotion recognition research and provide a tutorial to guide the researchers to start from the beginning. The scientific basis of EEG-based emotion recognition in the psychological and physiological levels is introduced. Further, we categorize these reviewed works into different technical routes and illustrate the theoretical basis and the research motivation, which will help the readers better understand why those techniques are studied and employed. At last, existing challenges and future investigations are also discussed in this paper, which guides the researchers to decide potential future research directions.

References in corpus (10)

• EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
• AutoML: A Survey of the State-of-the-Art
• Pre-trained Models for Natural Language Processing: A Survey
• Model-Agnostic Interpretability of Machine Learning
• Spatial-Temporal Recurrent Neural Network for Emotion Recognition
• Robust Spatial Filtering with Graph Convolutional Neural Networks
• Identifying Stable Patterns over Time for Emotion Recognition from EEG
• EEG-Based Emotion Recognition Using Regularized Graph Neural Networks
• Ultra Efficient Transfer Learning with Meta Update for Cross Subject EEG Classification
• Distilling EEG Representations via Capsules for Affective Computing

Cited by in corpus (8)

• Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion
• Enhanced Cross-Dataset Electroencephalogram-based Emotion Recognition using Unsupervised Domain Adaptation
• Multi-Source EEG Emotion Recognition via Dynamic Contrastive Domain Adaptation
• DEEMO: De-identity Multimodal Emotion Recognition and Reasoning
• ESI-GAL: EEG Source Imaging-based Trajectory Estimation for Grasp and Lift Task
• Thelxinoë: Recognizing Human Emotions Using Pupillometry and Machine Learning
• Towards Interactive Reinforcement Learning with Intrinsic Feedback
• Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks