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62311

Features Extraction of ECG Signals Using Wavelet Transforms

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Last updated: 04 Jan 2025

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Abstract

This paper introduces a proposed technique for extracting some of the important features of the electrocardiograph (ECG) signals. The proposed technique is based on the principles of the wavelet transforms (WT). In this work, special attention has been given to the arrhythmia diseases. The proposed approach has been tested using real ECG signals collected from some patients using a computer controlled multi channel data acquisition system. The measured features have been compared with the normal cases, which in turn have been compared with the standard features.

DOI

10.21608/iceeng.1999.62311

Keywords

Electrocardiograph (ECG), Wavelet Transforms (WT), Beat per Minute (BPM), Arrhythmia Diseases, Band Pass Filter (BPF), High Pass Filter (HPF), Low Pass Filter (LPF), and MIT/BIH Massachusetts Institute of Technology/Beth Israel Hospital arrhythmia database

Authors

First Name

M.

Last Name

Gadallah

MiddleName

E.

Affiliation

Associate professor, Dpt. of Electronic Engineering, Egyptian Armed forces.

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Orcid

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First Name

S.

Last Name

Alian

MiddleName

M.

Affiliation

Professor, Dpt. of Electronic Engineering, Egyptian Armed forces.

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Orcid

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First Name

Kh.

Last Name

Reda

MiddleName

M.

Affiliation

Eng., Egyptian Armed forces.

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Volume

2

Article Issue

2nd International Conference on Electrical Engineering ICEENG 1999

Related Issue

9420

Issue Date

1999-11-01

Receive Date

2019-11-27

Publish Date

1999-11-01

Page Start

166

Page End

176

Print ISSN

2636-4433

Online ISSN

2636-4441

Article File

ICEENG_Volume 2_Issue 2nd International Conference on Electrical Engineering ICE….pdf

PDF . 2.2MB

Link

https://iceeng.journals.ekb.eg/article_62311.html

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https://iceeng.journals.ekb.eg/service?article_code=62311

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Original Article

Type Code

833

Publication Type

Journal

Publication Title

The International Conference on Electrical Engineering

Publication Link

https://iceeng.journals.ekb.eg/

MainTitle

Features Extraction of ECG Signals Using Wavelet Transforms

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Article

Created At

22 Jan 2023