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ECG Noise Canceller: Studying and Performance Improvement under Different Algorithms

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Last updated: 24 Dec 2024

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Abstract

In Electrocardiogram (ECG) application, we face a main problem of power line noise added to the ECG signal. Different Researchers have been interested in this problem due to its importance. In this paper we introduce a study of different algorithms and their effects on the performance of the ECG noise canceller. We have used many kinds of algorithms such as: LMS (Least Mean Square), NLMS (Normalized Least Mean Square), Signed Regressor LMS (SRLMS), Sign LMS (SLMS), Sign-Sign LMS (SSLMS) and a new proposed modified LMS called Variable Step size Least Mean Square (VSLMS) using MATLAB software package as well as Unbiased Linear output Neural Network (ULNN) and Unbiased Non Linear output Neural Network (UNLNN). It is promising to clarify the difference among these algorithms with the aim of obtaining better performance.

DOI

10.21608/asat.2015.22920

Keywords

ECG signal, adaptive noise canceller, Neural network, power line interference

Authors

First Name

Ashraf

Last Name

Khalaf

MiddleName

A. M.

Affiliation

Department of Communication & Electronics, Faculty of Engineering, Minia University.

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First Name

M.

Last Name

Ibrahim

MiddleName

M.

Affiliation

Department of Communication & Electronics, Faculty of Engineering, Minia University.

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Orcid

-

First Name

Hesham

Last Name

Hamed

MiddleName

F. A.

Affiliation

Department of Communication & Electronics, Faculty of Engineering, Minia University.

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City

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Orcid

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First Name

M.

Last Name

Abdelghany

MiddleName

A.

Affiliation

Department of Communication & Electronics, Faculty of Engineering, Minia University.

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Orcid

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Volume

16

Article Issue

AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015

Related Issue

4316

Issue Date

2015-05-01

Receive Date

2018-12-26

Publish Date

2015-05-01

Page Start

1

Page End

18

Print ISSN

2090-0678

Online ISSN

2636-364X

Link

https://asat.journals.ekb.eg/article_22920.html

Detail API

https://asat.journals.ekb.eg/service?article_code=22920

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30

Type

Original Article

Type Code

737

Publication Type

Journal

Publication Title

International Conference on Aerospace Sciences and Aviation Technology

Publication Link

https://asat.journals.ekb.eg/

MainTitle

ECG Noise Canceller: Studying and Performance Improvement under Different Algorithms

Details

Type

Article

Created At

22 Jan 2023