On Harnessing EEG Signals for the Comprehensive Assessment of Neurological Disorders: A Review

Document Type

Article

Source of Publication

IEEE Transactions on Cognitive and Developmental Systems

Publication Date

1-1-2026

Abstract

Electroencephalography (EEG) is a scientific technique used to analyze and decode brain activity to identify different neurodegenerative diseases and psychiatric disorders. The insufficiency of specialists and neurologists is attributed to the prevalence of intricate disorders. Prompt and accurate diagnosis is crucial in managing any healthcare issue. EEG signal has shown its value in the prompt identification and prediction of diseases, hence providing valuable assistance to specialists and neurologists. This systematic review examines and analyzes the use of EEG signals for the diagnosis of different disorders and the identification of their biomarkers, drawing on existing research. The research aims to examine the use of EEG signals in the diagnostic process and determine whether a disorder may be predicted using EEG signals in advance. This raises novel research inquiries, which are investigated via 100 academic publications. Findings: EEG signals have been shown to be effective not only for early-stage diagnosis but also for predicting diseases and disorders before they arise, such as Bipolar detection, cancer detection, and the prediction of harmful brain activities. The results indicate that EEG signals can provide novel prospects for more exploration, such as the prediction and prognosis of diseases.

ISSN

2379-8920

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Disciplines

Computer Sciences

Keywords

classification, detection, diagnosis, diseases, EEG signals, prediction

Scopus ID

105032850414

Indexed in Scopus

yes

Open Access

no

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