Vectorcardiographic evaluation of myocardial infarct size: departure parameters are superior to conventional spatial parameters

Present results and methods of vectorcardiographic diagnostics of ischemic heart disease

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.

Model TJ-IV computer-assisted vectorcardiogram analysis system

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.