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209673

ECG Denoising using a Single-Node Dynamic Reservoir Computing Architecture.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Biomedical Engineering

Abstract

Accurate detection of heart disease requires purely realistic electrocardiogram (ECG) signals. In the process of acquisition and transmission, various noises destroy the clean ECG signal, making diagnosis difficult. Here, we apply a single node Reservoir computing (SNRC) architecture based on a recurrent neural network (RNN) to solve this problem by minimizing typical electromyogram noise (EMG) and power line interference (PLI) that damage the ECG signal. MIT-BIH, the standard online arrhythmia database, is used to collect data and test the quality of the proposed method. To evaluate the SNRC architecture, we use two performance indicators, namely, SNR output improvement (SNRimp) and the Percentage Root mean square Difference (PRD). The proposed SNRC architecture is superior to the latest technology and can achieve higher SNRimp and lower PRD for all types of typical ECG noise under study. These results indicate that the proposed SNRC architecture is expected to efficiently restore the dynamics of ECG signals in vivo

DOI

10.21608/bfemu.2021.209673

Keywords

Electrocardiogram, Reservoir Computing, denoising, Single node reservoir computing

Authors

First Name

Aya

Last Name

N. Elbedwehy

MiddleName

-

Affiliation

Researcher of Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 35516 Mansoura City, Egypt

Email

ayanagy@mans.edu.eg

City

-

Orcid

-

First Name

Mohy Eldin

Last Name

Abo-Elsoud

MiddleName

Ahmed

Affiliation

Professor of Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 35516 Mansoura City, Egypt

Email

mohyldin@gmail.com

City

-

Orcid

-

First Name

Ahmed

Last Name

Elnakib

MiddleName

-

Affiliation

Associate Professor of Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 35516 Mansoura City, Egypt

Email

nakib@mans.edu.eg

City

Masnoura

Orcid

0000-0001-6084-3622

Volume

46

Article Issue

4

Related Issue

28611

Issue Date

2021-12-01

Receive Date

2021-06-01

Publish Date

2021-12-18

Page Start

47

Page End

52

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 46_Issue 4_Pages 47-52.pdf

PDF . 884.2kB

Link

https://bfemu.journals.ekb.eg/article_209673.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=209673

Order

27

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023