@article{ART003397346},
author={Hyun-Ju Lee and Dong-Il Shin},
title={A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2026},
volume={31},
number={10},
pages={9-27}
TY - JOUR
AU - Hyun-Ju Lee
AU - Dong-Il Shin
TI - A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance
JO - Journal of The Korea Society of Computer and Information
PY - 2026
VL - 31
IS - 10
PB - The Korean Society Of Computer And Information
SP - 9
EP - 27
SN - 1598-849X
AB - This study proposes an SVM+PUK-LSTM hybrid model for EEG-based emotion recognition and evaluation of generalization to unseen subjects. Raw EEG signals from the DEAP dataset were resampled to 256Hz and processed into 3-s non-overlapping epochs, from which a 160-dimensional PSD feature vector was constructed using 32 EEG channels and five frequency bands; emotional states were defined into four Arousal–Valence-based classes: HAHV, HALV, LAHV, and LALV. The proposed model achieved an Accuracy of 98.42±3.82% and a Macro F1-score of 97.55±6.31% under 10-fold cross-validation, and an Accuracy of 90.11±7.91% and a Macro F1-score of 88.38±11.04% under 32-fold subject-independent LOSO evaluation. Under the same LOSO protocol and random seed of 1, comparisons with standalone LSTM and SVM+RBF-LSTM showed statistically significant differences in Accuracy using the Wilcoxon signed-rank test with Holm–Bonferroni correction. These results demonstrate the proposed model's 4-class EEG emotion classification performance and potential for generalization to unseen subjects.
KW - EEG-based Emotion Recognition;SVM-LSTM Hybrid Model;DEAP Dataset;Subject-Independent Evaluation;Leave-One-Subject-Out(LOSO)
DO -
UR -
ER -
Hyun-Ju Lee and Dong-Il Shin. (2026). A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance. Journal of The Korea Society of Computer and Information, 31(10), 9-27.
Hyun-Ju Lee and Dong-Il Shin. 2026, "A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance", Journal of The Korea Society of Computer and Information, vol.31, no.10 pp.9-27.
Hyun-Ju Lee, Dong-Il Shin "A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance" Journal of The Korea Society of Computer and Information 31.10 pp.9-27 (2026) : 9.
Hyun-Ju Lee, Dong-Il Shin. A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance. 2026; 31(10), 9-27.
Hyun-Ju Lee and Dong-Il Shin. "A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance" Journal of The Korea Society of Computer and Information 31, no.10 (2026) : 9-27.
Hyun-Ju Lee; Dong-Il Shin. A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance. Journal of The Korea Society of Computer and Information, 31(10), 9-27.
Hyun-Ju Lee; Dong-Il Shin. A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance. Journal of The Korea Society of Computer and Information. 2026; 31(10) 9-27.
Hyun-Ju Lee, Dong-Il Shin. A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance. 2026; 31(10), 9-27.
Hyun-Ju Lee and Dong-Il Shin. "A SVM-LSTM Hybrid Model for Improving EEG-Based Emotion Recognition Performance" Journal of The Korea Society of Computer and Information 31, no.10 (2026) : 9-27.
