EEG Innovations in Neurological Disorder Diagnostics: A Five-Year Review
Madhuchhanda Basak, Diptadip Maiti, Debashis Das
Asian Journal of Research in Computer Science · pp. 226–249 · Published 23 May 2024
10.9734/ajrcos/2024/v17i6470Abstract
The study provides a description of electroencephalography (EEG) advancements and their application in diagnosing and assessing various neurological diseases over the previous five years. The paper covers how EEG is used to examine epilepsy, sleep disorders, movement disorders, cognitive function, and brain damage. In epilepsy, EEG remains critical for seizure diagnosis, categorization, and localization of epileptogenic zones. Recent enhancements include the integration of machine learning techniques with high-density EEG equipment. In terms of sleep disorders, aberrant patterns suggestive of illnesses such as sleep apnea or narcolepsy may be diagnosed by a sleep architecture study utilizing EEGs, which can also be used to track therapy response. Cortical involvement occurs in Parkinson’s disease and Huntington’s disease, as well as other areas of the brain stem or basal ganglia. It helps researchers learn more about the cortical damage produced by these disorders, which contributes greatly to understanding their pathophysiology. Aside from that, cognitive evaluation based on EEG has evolved via the creation of quantifiable biomarkers for early identification and monitoring of deterioration in Alzheimer’s disease, among others. Traumatic injuries can damage brain functioning, hence knowledge regarding severity predicted outcomes can be acquired by Traumatic Brain Injury evaluation utilizing EEG.
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