Developing an EEG-Based Emotion Recognition Using Ensemble Deep Learning Methods and Fusion of Brain Effective Connectivity Maps

• Published in: IEEE access Vol. 12; pp. 50949 - 50965
• Main Authors: Bagherzadeh, Sara, Shalbaf, Ahmad, Shoeibi, Afshin, Jafari, Mahboobeh, Tan, Ru-San, Acharya, U. Rajendra
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Arousal; Artificial neural networks; Brain modeling; Datasets; Deep learning; Effective connectivity; Electroencephalography; Emotion recognition; Emotional factors; Emotions; Feature extraction; Human-computer interface; Image classification; Information flow; Long short term memory; Machine learning; Medical imaging; Time-frequency analysis; Transfer functions; Transfer learning; Two dimensional models

The objective of this paper is to develop a novel emotion recognition system from electroencephalogram (EEG) signals using effective connectivity and deep learning methods. Emotion recognition is an important task for various applications such as human-computer interaction and, mental health diagnos...