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DOI Prefix: 10.47001/IRJIET

Epileptic Seizures Detection Using Machine Learning: A Review

Abdulrahman Talal IbrahimDepartment of Computer Science, College of Computer Science and Mathematics, University of Mosul, Mosul, IraqAmera Istiqlal BadranDepartment of Computer Science, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq

Vol 8 No 7 (2024): Volume 8, Issue 7, July 2024 | Pages: 167-171

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 30-07-2024

doi Logo doi.org/10.47001/IRJIET/2024.807018

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Abstract

These episodes may be attributed to abnormal chemical alterations in the brain or anomalies in the cerebral region. These illnesses are classified as chronic and increase the likelihood of death due to their abrupt onset and absence of preceding symptoms. Seizures can be identified by analyzing the brain signals produced by neuronal cells. Traditionally, electroencephalogram (EEG) recordings a multi-channel depiction of brain neuronal activity is used for brain signal monitoring. This paper examines important advancements made in the analysis of EEG waveforms to create predictive algorithms for epilepsy.

Keywords

Machine learning, electroencephalogram (EEG), Epileptic seizures, Support Vector Machine, SVM


Citation of this Article

Abdulrahman Talal Ibrahim, & Amera Istiqlal Badran. (2024). Epileptic Seizures Detection Using Machine Learning: A Review. International Research Journal of Innovations in Engineering and Technology - IRJIET, 8(7), 167-171, Article DOI https://doi.org/10.47001/IRJIET/2024.807018

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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