Selected transformation methods and their comparison for VCG leads deriving
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10247940" target="_blank" >RIV/61989100:27240/22:10247940 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S1110016821005834" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1110016821005834</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.aej.2021.08.068" target="_blank" >10.1016/j.aej.2021.08.068</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Selected transformation methods and their comparison for VCG leads deriving
Popis výsledku v původním jazyce
Vectorcardiography (VCG) as an alternative form of 12-lead ECG is another method of measuring the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common, but VCG leads can be derived from 12-lead ECG. VCG has proven to be a useful and more accurate tool for diagnosing various heart diseases within automated detection. This paper presents the application of four transformation methods namely: Kors regression, IDT, QLSV and Quasi-Orthogonal transformation to obtain a derived VCG. A total of 20 physiological and 20 records with the diagnosis of myocardial infarction were used. For physiological records, the Kors regression method achieved the best results in leads X and Y with relative deviation <1%, correlation and percentage similarity >99%. In lead Z, the QLSV method achieved the most accurate results with relative deviation <1%, correlation >98% and percentage similarity >99%. For pathological records, the most accurate method in all leads was Kors regression with relative deviation <2.2%, correlation >93% and percentage similarity >97%. From these results, there is the possibility of creating a new transformation method from the existing ones in order to obtain a more accurate transformation. (C) 2021 THE AUTHORS
Název v anglickém jazyce
Selected transformation methods and their comparison for VCG leads deriving
Popis výsledku anglicky
Vectorcardiography (VCG) as an alternative form of 12-lead ECG is another method of measuring the electrical activity of the heart. The use of vectorcardiography in clinical practice is not common, but VCG leads can be derived from 12-lead ECG. VCG has proven to be a useful and more accurate tool for diagnosing various heart diseases within automated detection. This paper presents the application of four transformation methods namely: Kors regression, IDT, QLSV and Quasi-Orthogonal transformation to obtain a derived VCG. A total of 20 physiological and 20 records with the diagnosis of myocardial infarction were used. For physiological records, the Kors regression method achieved the best results in leads X and Y with relative deviation <1%, correlation and percentage similarity >99%. In lead Z, the QLSV method achieved the most accurate results with relative deviation <1%, correlation >98% and percentage similarity >99%. For pathological records, the most accurate method in all leads was Kors regression with relative deviation <2.2%, correlation >93% and percentage similarity >97%. From these results, there is the possibility of creating a new transformation method from the existing ones in order to obtain a more accurate transformation. (C) 2021 THE AUTHORS
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
20202 - Communication engineering and systems
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Alexandria Engineering Journal
ISSN
1110-0168
e-ISSN
—
Svazek periodika
Volume 61
Číslo periodika v rámci svazku
5
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
11
Strana od-do
3475-3485
Kód UT WoS článku
—
EID výsledku v databázi Scopus
2-s2.0-85114908924