EEG Emotion Recognition

8 papers with code • 2 benchmarks • 2 datasets

Emotion Recognition using EEG signals


Most implemented papers

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

zhongpeixiang/RGNN 18 Jul 2019

Finally, investigations on the neuronal activities reveal important brain regions and inter-channel relations for EEG-based emotion recognition.

LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface

yi-ding-cs/LGG 5 May 2021

It captures temporal dynamics of EEG which then serves as input to the proposed local and global graph-filtering layers.

MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition

VoiceBeer/MS-MDA 16 Jul 2021

Although several studies have adopted domain adaptation (DA) approaches to tackle this problem, most of them treat multiple EEG data from different subjects and sessions together as a single source domain for transfer, which either fails to satisfy the assumption of domain adaptation that the source has a certain marginal distribution, or increases the difficulty of adaptation.

Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism

meiyor/deep-learning-emotion-decoding-using-eeg-data-from-autism-individuals 25 Nov 2021

This study is the first to consolidate a more transparent feature-relevance calculation for a successful EEG-based facial emotion recognition using a within-subject-trained CNN in typically-developed and ASD individuals.

GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

chen-xdu/gmss 12 Apr 2022

GMSS has the ability to learn more general representations by integrating multiple self-supervised tasks, including spatial and frequency jigsaw puzzle tasks, and contrastive learning tasks.