Review of Processing Pathological Vectorcardiographic Records for the Detection of Heart Disease

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10251913" target="_blank" >RIV/61989100:27240/22:10251913 - isvavai.cz</a>

Result on the web

<a href="https://www.frontiersin.org/articles/10.3389/fphys.2022.856590/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fphys.2022.856590/full</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fphys.2022.856590" target="_blank" >10.3389/fphys.2022.856590</a>

Result language

angličtina

Original language name

Review of Processing Pathological Vectorcardiographic Records for the Detection of Heart Disease

Original language description

Vectorcardiography (VCG) is another useful method that provides us with useful spatial information about the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common nowadays, mainly due to the well-established 12-lead ECG system. However, VCG leads can be derived from standard 12-lead ECG systems using mathematical transformations. These derived or directly measured VCG records have proven to be a useful tool for diagnosing various heart diseases such as myocardial infarction, ventricular hypertrophy, myocardial scars, long QT syndrome, etc., where standard ECG does not achieve reliable accuracy within automated detection. With the development of computer technology in recent years, vectorcardiography is beginning to come to the forefront again. In this review we highlight the analysis of VCG records within the extraction of functional parameters for the detection of heart disease. We focus on methods of processing VCG functionalities and their use in given pathologies. Improving or combining current or developing new advanced signal processing methods can contribute to better and earlier detection of heart disease. We also focus on the most commonly used methods to derive a VCG from 12-lead ECG.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Frontiers in Physiology

ISSN

1664-042X

e-ISSN

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Volume of the periodical

13

Issue of the periodical within the volume

13/2022

Country of publishing house

CH - SWITZERLAND

Number of pages

21

Pages from-to

nestrankovano

UT code for WoS article

000804769900001

EID of the result in the Scopus database

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