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357471

Analysis Techniques and Feature Extraction on ECG: A Review

Article

Last updated: 21 Dec 2024

Subjects

-

Tags

Computer science

Abstract

Electrocardiogram (ECG) is an inconsistent signal that is used to measure the heart rate. Electrocardiogram is used recently to identify people and protect data as an optimal solution. It can also be used in unimodal and multimodal systems. One of the advantages of using an electrocardiogram is that the person is still alive. This makes plagiarism more difficult compared to any other biometric feature. Doctors can diagnose diseases by comparing the shape and pattern of signals. To diagnose a patient by recording an ECG. Noise is removed in order to obtain a better evaluation. We find that extract ECG is of great importance in diagnosing heart diseases and human recognition. One of the ECG cardiac sessions is made up of P-QRS-T waves. To determine the time and amplitude periods in the ECG by extracting the features or other features are analyzed at a later time. In this verse we will list the ECG techniques and their analysis.

DOI

10.21608/sjfsmu.2024.357471

Keywords

Electrocardiogram, Biometrics, P-QRS-T waves

Authors

First Name

Mariana

Last Name

Basoum

MiddleName

-

Affiliation

Assistant Professor at Mathematics and Computer Science Department, Faculty of Science, Menoufia University

Email

marianabarsoum0@gmail.com

City

-

Orcid

-

First Name

Ibrahim

Last Name

Omara

MiddleName

-

Affiliation

Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Egypt

Email

-

City

-

Orcid

-

First Name

Mohamed

Last Name

Khalaf

MiddleName

-

Affiliation

Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Egypt

Email

-

City

-

Orcid

-

Volume

28

Article Issue

1

Related Issue

47496

Issue Date

2024-06-01

Receive Date

2024-01-03

Publish Date

2024-06-01

Page Start

1

Page End

8

Print ISSN

3062-469X

Online ISSN

3009-6367

Link

https://sjfsmu.journals.ekb.eg/article_357471.html

Detail API

https://sjfsmu.journals.ekb.eg/service?article_code=357471

Order

357,471

Type

Original Article

Type Code

3,141

Publication Type

Journal

Publication Title

Scientific Journal of Faculty of Science, Menoufia University

Publication Link

https://sjfsmu.journals.ekb.eg/

MainTitle

Analysis Techniques and Feature Extraction on ECG: A Review

Details

Type

Article

Created At

21 Dec 2024