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117594

A DEDICATED DIAGNOSTIC DISTORTION MEASURE FOR THE EVALUATION OF ECG SIGNAL COMPRESSION TECHNIQUES ADOPTED FOR REMOTE DIAGNOSIS OF CARDIOVASCULAR DISEASES

Article

Last updated: 26 Dec 2024

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Subjects

-

Tags

Electrical Engineering, Computer Engineering and Electrical power and machines engineering.

Abstract

In the current century diseases of the heart, brain and blood vessels, termed Cardiovascular Diseases (CVDs), represent the main death reasons [1-2]. The CVDs can be diagnosed through the usage of the features extracted from the P-waves, PR-intervals, QRS-complexes, ST-segments, T- and U-waves. The irregularity of beat phases is generally called arrhythmia and some arrhythmias are very dangerous for patients. The types of arrhythmias that can be diagnosed using the Electrocardiogram (ECG) features include: sinus bradycardia, ventricular tachycardia, sinus arrhythmia, atrial premature contraction. In addition, right and left bundle branch block, atrial fibrillation and flutter, heart block as well as coronary artery diseases such as ST- and non ST-elevation myocardial infarction can be diagnosed using ECG signal features. This paper introduces automatic ECG signal interpretations adopted for detecting CVDs. It investigates the effect of compressing the ECG signals on evaluating the performance of diagnosing CVDs. This has been performed by introducing a Dedicated Diagnostic Distortion Measure (3DM) that is based on comparing the complex features of the original and the reconstructed ECG signals while keeping a pre-determined diagnostic error and good reconstructed signal quality. In fact, the allowable pre-determined diagnostic error is a disease dependent. The diagnostic features considered in this paper include duration features, amplitude features and shape features. Consultations with cardiologists through Mean Opinion Score (MOS) test show that the proposed 3DM is most informative compared to the well-known percentage root-mean square difference in the evaluation of compression techniques oriented for CVDs diagnosing. The price paid for the usage of 3DM as a good performance metric is the computational complexity in calculating the diagnostic features. However, the calculated features can be adopted for diagnosing purposes.

DOI

10.21608/jesaun.2016.117594

Keywords

ECG compression, Telediagnoses and Telemonitoring, Cardiovascular disease, Arrhythmias, Blood vessels, MOS test

Authors

First Name

Mohamed M.

Last Name

Abo-Zahhad

MiddleName

-

Affiliation

Engineer at Assiut University, Assiut, Egypt

Email

eng_mmz_eg@yahoo.com

City

-

Orcid

-

First Name

Aziza I.

Last Name

Hussein

MiddleName

-

Affiliation

Computer and Systems Department, Faculty of Engineering, Minia University, Minia, Egypt

Email

-

City

-

Orcid

-

First Name

Abdelfatah M.

Last Name

Mohamed

MiddleName

-

Affiliation

Electrical and Electronics Eng. Depat., Faculty of Engineering, Assiut University, Assiut, Egypt and in a secondment to Electrical and Computer Eng. Dept., Effat University

Email

afmm52@yahoo.com

City

-

Orcid

-

First Name

Ahmed M.

Last Name

El-Sawy

MiddleName

-

Affiliation

Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt

Email

-

City

-

Orcid

-

Volume

44

Article Issue

No 2

Related Issue

16844

Issue Date

2016-03-01

Receive Date

2016-02-23

Publish Date

2016-03-01

Page Start

158

Page End

174

Print ISSN

1687-0530

Online ISSN

2356-8550

Article File

JESAUN_Volume 44_Issue No 2_Pages 158-174.pdf

PDF . 1.2MB

Link

https://jesaun.journals.ekb.eg/article_117594.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=117594

Order

4

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

A DEDICATED DIAGNOSTIC DISTORTION MEASURE FOR THE EVALUATION OF ECG SIGNAL COMPRESSION TECHNIQUES ADOPTED FOR REMOTE DIAGNOSIS OF CARDIOVASCULAR DISEASES

Details

Type

Article

Created At

23 Jan 2023