A systematic literature review of emotion recognition using EEG signals
In this study, we conducted a systematic literature review of 107 primary studies conducted
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …
Spatial–temporal features-based EEG emotion recognition using graph convolution network and long short-term memory
F Zheng, B Hu, X Zheng, Y Zhang - Physiological Measurement, 2023 - iopscience.iop.org
Objective. Emotion recognition on the basis of electroencephalography (EEG) signals has
received a significant amount of attention in the areas of cognitive science and human …
received a significant amount of attention in the areas of cognitive science and human …
Multi-Domain Based Dynamic Graph Representation Learning for EEG Emotion Recognition
Graph neural networks (GNNs) have demonstrated efficient processing of graph-structured
data, making them a promising method for electroencephalogram (EEG) emotion …
data, making them a promising method for electroencephalogram (EEG) emotion …
A Siamese Network Fusion Time-Frequency Domain Features for Mental Workload Level Identification
J Yan, D Li, J Deng, H Wang, Z Long… - 2022 4th …, 2022 - ieeexplore.ieee.org
Mental workload level can reflect subjects' personal ability. In addition, continuous high level
of mental workload can reduce subjects' performance level, so it is necessary to detect …
of mental workload can reduce subjects' performance level, so it is necessary to detect …