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Kijonka J, Vavra P, Penhaker M, Bibbo D, Kudrna P, Kubicek J. Present results and methods of vectorcardiographic diagnostics of ischemic heart disease. Comput Biol Med 2024; 169:107781. [PMID: 38103481 DOI: 10.1016/j.compbiomed.2023.107781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/03/2023] [Accepted: 11/28/2023] [Indexed: 12/19/2023]
Abstract
This article presents an overview of existing approaches to perform vectorcardiographic (VCG) diagnostics of ischemic heart disease (IHD). Individual methodologies are divided into categories to create a comprehensive and clear overview of electrical cardiac activity measurement, signal pre-processing, features extraction and classification procedures. An emphasis is placed on methods describing the electrical heart space (EHS) by several features extraction techniques based on spatiotemporal characteristics or signal modelling and signal transformations. Performance of individual methodologies are compared depending on classification of extent of ischemia, acute forms - myocardial infarction (MI) and myocardial scars localization. Based on a comparison of imaging methods, the advantages of VCG over the standard 12-leads ECG such as providing a 3D orthogonal leads imaging, better performance, and appropriate computer processing are highlighted. The issues of electrical cardiac activity measurements on body surface, the lack of VKG databases supported by a more accurate imaging method, possibility of comparison with the physiology of individual cases are outlined as potential reserves for future research.
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Affiliation(s)
- Jan Kijonka
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17.listopadu 15, Ostrava, Poruba, 708 00, Czech Republic.
| | - Petr Vavra
- Department of Surgical Studies, Faculty of Medicine of the University of Ostrava, Syllabova 19, 703 00, Ostrava 3, Czech Republic; Surgery Clinic, University Hospital Ostrava, 17. listopadu 13, Ostrava, Czech Republic.
| | - Marek Penhaker
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17.listopadu 15, Ostrava, Poruba, 708 00, Czech Republic; Faculty of Electrical Engineering and Information Technology, University of Zilina, Zilina, Czech Republic.
| | - Daniele Bibbo
- Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Via Vito Volterra, 62, 00146, Rome, Italy.
| | - Petr Kudrna
- Department of Biomedical Technology, Faculty of Biomedical Engineering, Czech Technical University in Prague, Nam. Sitna 3105, 272 01, Kladno, Czech Republic.
| | - Jan Kubicek
- Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, 17.listopadu 15, Ostrava, Poruba, 708 00, Czech Republic.
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Frontal Plane Vectorcardiograms: Theory and Graphics Visualization of Cardiac Health Status. J Med Syst 2009; 34:445-58. [DOI: 10.1007/s10916-009-9257-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2008] [Accepted: 01/21/2009] [Indexed: 10/21/2022]
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Guo X, Jue X, Ruan Y, Wang Z. Model TJ-IV computer-assisted vectorcardiogram analysis system. JOURNAL OF TONGJI MEDICAL UNIVERSITY = TONG JI YI KE DA XUE XUE BAO 2004; 21:21-2, 81. [PMID: 11523238 DOI: 10.1007/bf02888027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
During last 16 years we have successfully developed the computer-assisted vectorcardiogram analysis systems: model TJ-I, TJ-II, and TJ-III, but some technical problems remained unresolved, such as the recognition accuracy for vectorcardiograms, measurement of the parameters of complicated QRS waves, the ratio of T loop length to width, and the area of spatial vectors etc. A new system, model TJ-IV was designed to resolve these technical problems. The system was equipped with a 586 computer with a CPU of 120 MHz. Special new low-noise amplifier was employed and C language was used for programming. Three graph recognition techniques were used to enhance the accuracy of VCG recognition. 32 orthogonal electrocardiograms and vectorcardiograms were displayed and printed, and 566 parameters of vectorcardiograms were calculated. Our results with 150 cases showed that the system had high accuracy of graph recognition, and parameter calculation and the results were essentially consistent with those of manipulative methods. We were led to concluded when compared with TJ-III system, the new version has higher accuracy of processing and measurement for vectorcardiograms, is able to process more vectorcardiographic parameters, with higher processing speed.
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Affiliation(s)
- X Guo
- Department of Cardiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030
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