The Role of EEG as Neuro-Markers for Patients with Depression: A Systematic Review

Depressive symptoms may include feelings of melancholy, lack of interest, and difficulty remembering and focusing. The existing techniques of detecting depression need a lot of interaction with humans, and the findings are highly reliant on the knowledge and skill of the doctor doing them. Electroencephalography ( EEG ) is a potential tool that reveals interesting information that can be used in diagnosis and evaluation of human beings’ brain abnormalities with excellent time resolution; however, detecting depression is a challenge for engineers and scientists to support personalized health care. However, EEG may provide an idea of cognitive decline toward depression classification. To create a neurophysiological diagnostic index for therapeutic use that is sensitive to the severity of depression, it may be possible to combine the EEG with other biological, cognitive markers, and imaging methods. The goal of the current study is to emphasize baseline EEG activity in depressed individuals, beginning with EEG signal collection and continuing through EEG data preprocessing steps for signal augmentation, linear and nonlinear properties. The subsequent focus will be on EEG signal extraction to account for the large swings of EEG signals, followed by classification approaches to differentiate the severity of depression. Therefore, the present review has examined the role of EEG signal processing and analysis in helping medical doctors and clinicians to determine suitable planning and optimal, more effective treatment programs.