Detection of concurrent atrial ischemia with continuous monitoring of dynamic PR-segment changes in patients with acute myocardial infarction

Korhonen, Päivi; Väisänen, Juho; Nousiainen, J.; Huhtala, Heini; Yli‐Mäyry, Sinikka; Raatikainen, Pekka

doi:10.1016/j.jelectrocard.2013.03.013

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…Also the higher sensitivity of VCG in detection in patients with inferior infarction is mentioned Hurd et al (1981), Edenbrand et al (1990). By evaluating certain sections of the heart cycle, such as PR Korhonen et al (2013) or ST Kawahito et al (2003), Eriksson et al (2007), El Haddad et al (2016, Fesmire et al (2002), Romero et al (2010), Matveev et al (2007), Hernandez et al (2018), it is possible to develop identification methods for further detection of heart disease. Study dealing with changes in the PR segment of the heart cycle by Jim et al (2006) inspired Korhonen et al (2013) to evaluate dynamic PR segment changes for 37 patients with AMI.…”

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confidence: 99%

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

Vondrak

Penhaker

2022

Front. Physiol.

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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.

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