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October 23, 2025Al-Iraqia Journal of Scientific Engineering ResearchOpen Access

Harnessing Deep Learning for EEG Emotion Recognition: A Hybrid Approach with Attention Mechanisms

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Authors

AAAli H. AbdulwahhabAltınbaş UniversityAAAlaa Hussein AbdulaalUrmia University of TechnologyAJAli M. JasimNational Aerospace University – Kharkiv Aviation Institute

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Implication

Hybrid model improves emotion recognition accuracy in EEG signals, indicating potential applications in brain-computer interfaces.

Key Points

  • Model achieved a macro-average F1-score of 93% on the SEED-IV dataset, validating its effectiveness.
  • The architecture integrates convolutional neural networks, LSTM networks, and attention mechanisms for better feature extraction.
  • Utilization of continuous wavelet transform and power spectral density enhances the model's capability under noisy conditions.
  • This hybrid approach may enable advancements in adaptive neurofeedback systems for emotion-aware technology.

Cite This Study

Abdulwahhab et al. (2025) studied this question.

synapsesocial.com/papers/68f9d6583f378872224924f6https://doi.org/10.58564/ijser.4.2.2025.323
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