Abstract

The electroencephalogram, or EEG, plays a significant part in the operation of electronic healthcare systems, particularly in the field of mental healthcare, which places a premium on continuous monitoring that is as unobtrusive as possible. Signals on an EEG may be interpreted to indicate activity going on in a person's brain as well as distinct emotional states. A sensation of mental or bodily strain is what we refer to as stress. It might be anything—an experience or a thought—that provokes feelings of agitation, anger, or nervousness in you. Mental stress has emerged as a significant problem in modern society and has the potential to lead to functional incapacity in the workplace. The study of electroencephalogram (EEG) signals may benefit from the use of a machine learning (ML) framework. This article provides an overview of the categorization of depression patients based on EEG.

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