Advances in EEG-Based Emotion Recognition: Methods and Challenges

Jiayu Yang

2025

Abstract

EEG-Based emotion recognition is a key area in affective computing and brain-computer interfaces (BCI), offering real-time insights into human emotional states. Unlike facial expressions or speech, EEG provides direct neural activity data, making it a robust tool for emotion decoding. However, several challenges hinder its effectiveness, including low signal-to-noise ratio (SNR), individual variability, and dataset inconsistencies. These issues affect model generalizability and classification accuracy, limiting real-world applications. This review is about the preprocessed EEG, machine as well as deep models, as well as cross-dataset generalization challenges. Comparative evaluation with traditional models such as SVM as well as the PCA is given with the implementation of the deep models such as the CNNs, LSTMs, as well as the implementation of the Transformer. Cross-subject variance reduction as well as standardization of databases is necessary for the advancement of emotional decoding with the use of the EEG. Future research should be targeted toward light models of AI, as well as the implementation of multiple modes as well as the domain adaptation.

Paper Citation

in Harvard Style

Yang J. (2025). Advances in EEG-Based Emotion Recognition: Methods and Challenges. In Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS; ISBN 978-989-758-789-4, SciTePress, pages 46-52. DOI: 10.5220/0014386500004933

in Bibtex Style

@conference{befs25,
author={Jiayu Yang},
title={Advances in EEG-Based Emotion Recognition: Methods and Challenges},
booktitle={Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS},
year={2025},
pages={46-52},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014386500004933},
isbn={978-989-758-789-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS
TI - Advances in EEG-Based Emotion Recognition: Methods and Challenges
SN - 978-989-758-789-4
AU - Yang J.
PY - 2025
SP - 46
EP - 52
DO - 10.5220/0014386500004933
PB - SciTePress