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64927

Literature Review on EEG Preprocessing, Feature Extraction, and Classifications Techniques

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Last updated: 25 Dec 2024

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Abstract

Classification is one of the main applications of machine learning, which can group and classify the cases based on learning and development using the available data and experience knowledge. Classification is used widely in biological and medical aspects. This paper presents the problem of electroencephalogram (EEG) signal classification. Classification is the step of identifying groups or classes based on similarities between them. This step is essential to differentiate between seizure and normal periods. EEG is a monitoring tool to determine the electrical activity of the brain. The nature of EEG is quite long, so it consumes time and very difficult in processing. Epilepsy is an illness that affects people of all ages, both cases males and females. Epilepsy is a neurological disorder that makes the activities of the brain abnormal and generates seizures. Seizure symptoms vary from one people to another; it depends on the location of epileptic discharge in the cortex. To speed up the classification process and make it efficient, EEG signal needs to be preprocessed. This paper reviews the epilepsy mentality disorder and the types of seizure, preprocessing operations that performed on EEG data, a common extracted feature from the signal, and detailed view on classification techniques that can be used in this problem.

DOI

10.21608/mjeer.2019.64927

Keywords

Epilepsy, EEG, preprocessing, features extraction, classification

Authors

First Name

Athar

Last Name

Shoka

MiddleName

-

Affiliation

Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Egypt

Email

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City

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Orcid

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First Name

Mohamed

Last Name

Dessouky

MiddleName

-

Affiliation

Computer Science and Engineering Faculty of Electronic Engineering Menofia University Egypt

Email

-

City

-

Orcid

-

First Name

Ahmed

Last Name

El-Sherbeny

MiddleName

-

Affiliation

Industrial Electronics And Control Engineering, Faculty of Electronic Engineering Menofia University Egypt

Email

-

City

-

Orcid

-

First Name

Ayman

Last Name

El-Sayed

MiddleName

-

Affiliation

Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Egypt

Email

ayman.elsayed@el-eng.menofia.edu.eg

City

Menouf

Orcid

0000-0002-4437-259X

Volume

28

Article Issue

ICEEM2019-Special Issue

Related Issue

9704

Issue Date

2019-12-01

Receive Date

2019-12-12

Publish Date

2019-12-01

Page Start

292

Page End

299

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_64927.html

Detail API

https://mjeer.journals.ekb.eg/service?article_code=64927

Order

8

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Literature Review on EEG Preprocessing, Feature Extraction, and Classifications Techniques

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Article

Created At

22 Jan 2023