Detecting mild depression from EEG signal in a non-clinical environment using machine learning technique

• Main Authors: Thulasi, K., Balakrishnan, Sumathi, Yap, Jia Suan, Yan, Xiao Qing, Malarvili, M. B., Murugesan, R. K., Devandran, Pagupathi
• Format: Conference or Workshop Item
• Published: 2023
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/107700/; http://dx.doi.org/10.1109/NBEC58134.2023.10352586

Depression can be detected through screening tests and non-invasive examinations at specific clinics, yet a professional must verify the severity. If mild depressions are not detected, it can lead to major depressions. Eventually, this could also be fatal. Collectively, the studies from the literatu...