A review on evaluating mental stress by deep learning using EEG signals

• Published in: Neural computing & applications Vol. 36; no. 21; pp. 12629 - 12654
• Main Authors: Badr, Yara, Tariq, Usman, Al-Shargie, Fares, Babiloni, Fabio, Al Mughairbi, Fadwa, Al-Nashash, Hasan
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2024; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Deep learning; Electroencephalography; Graph neural networks; Graphical representations; Image Processing and Computer Vision; Machine learning; Medical imaging; Neural networks; Probability and Statistics in Computer Science; Psychological stress; Review; Deep learning; CNN; Hybrid model; LSTM; EEG; Mental stress

Mental stress is a common problem that affects individuals all over the world. Stress reduces human functionality during routine work and may lead to severe health defects. Early detection of stress is important for preventing diseases and other negative health-related consequences of stress. Severa...