Convolutional Neural Network Approach for EEG-based Emotion Recognition using Brain Connectivity and its Spatial Information
Emotion recognition based on electroencephalography (EEG) has received attention as a way to implement human-centric services. However, there is still much room for improvement, particularly in terms of the recognition accuracy. In this paper, we propose a novel deep learning approach using convolutional neural networks (CNNs) for EEG-based emotion recognition. In particular, we employ brain connectivity features that have not been used with deep learning models in previous studies, which can account for synchronous activations of different brain regions. In addition, we develop a method to effectively capture asymmetric brain activity patterns that are important for emotion recognition. Experimental results confirm the effectiveness of our approach.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep LearningEEGElectroencephalogram (EEG)Emotion RecognitionSimilar Papers 제목 키워드 기반
Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks
Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-…
ClassificationEEGElectroencephalogram (EEG)General Classification+1Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition
Compared with the rich studies on the motor brain-computer interface (BCI), the recently emerging affective BCI presents distinct challenges since the brain functional connectivity networks involving emotion are not well…
Brain Computer InterfaceClusteringEEGElectroencephalogram (EEG)+3MSGM: A Multi-Scale Spatiotemporal Graph Mamba for EEG Emotion Recognition
EEG-based emotion recognition struggles with capturing multi-scale spatiotemporal dynamics and ensuring computational efficiency for real-time applications. Existing methods often oversimplify temporal granularity and sp…
Computational EfficiencyEEG Emotion RecognitionEmotion ClassificationA Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective
Compared to other modalities, electroencephalogram (EEG) based emotion recognition can intuitively respond to emotional patterns in the human brain and, therefore, has become one of the most focused tasks in affective co…
EEGElectroencephalogram (EEG)Emotion Recognition4D Attention-based Neural Network for EEG Emotion Recognition
Electroencephalograph (EEG) emotion recognition is a significant task in the brain-computer interface field. Although many deep learning methods are proposed recently, it is still challenging to make full use of the info…
Brain Computer InterfaceEEGEEG Emotion RecognitionElectroencephalogram (EEG)+1