Research Article

Review of EEG-based Classification of Depression Patients

by  Yasmeen Anis, Kaptan Singh, Amit Saxena
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Issue 2
Published: Apr 2023
Authors: Yasmeen Anis, Kaptan Singh, Amit Saxena
10.5120/ijca2023922677
PDF

Yasmeen Anis, Kaptan Singh, Amit Saxena . Review of EEG-based Classification of Depression Patients. International Journal of Computer Applications. 185, 2 (Apr 2023), 42-46. DOI=10.5120/ijca2023922677

                        @article{ 10.5120/ijca2023922677,
                        author  = { Yasmeen Anis,Kaptan Singh,Amit Saxena },
                        title   = { Review of EEG-based Classification of Depression Patients },
                        journal = { International Journal of Computer Applications },
                        year    = { 2023 },
                        volume  = { 185 },
                        number  = { 2 },
                        pages   = { 42-46 },
                        doi     = { 10.5120/ijca2023922677 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2023
                        %A Yasmeen Anis
                        %A Kaptan Singh
                        %A Amit Saxena
                        %T Review of EEG-based Classification of Depression Patients%T 
                        %J International Journal of Computer Applications
                        %V 185
                        %N 2
                        %P 42-46
                        %R 10.5120/ijca2023922677
                        %I Foundation of Computer Science (FCS), NY, USA
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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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

EEG Emotion Stress Machine Learning E-healthcare

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