Development of cardioanalyzer for differential diagnosis of Myocardial Infarction
Development of a cardiac analyzer for differential diagnosis of an Acute Myocardial Infarction and its complications with the complete planimetric description of ECG signal evolution in natural language
Tech Area / Field
- MED-DID/Diagnostics & Devices/Medicine
- INF-DAT/Data Storage and Peripherals/Information and Communications
- INF-SIG/Sensors and Signal Processing/Information and Communications
- INF-SOF/Software/Information and Communications
- INS-MEA/Measuring Instruments/Instrumentation
3 Approved without Funding
VNIITF, Russia, Chelyabinsk reg., Snezhinsk
- Institute for Computer Aided Design, Russia, Moscow
- Georgia Institute of Technology, USA, GA, Atlanta\nCardiology clinic of the Bad Soden district hospital, the Academic study hospital of the Frankfurt am Main University, Germany, Bad Soden
Project summaryThe purpose of the given project - creation essentially new digital cardio-analyzer.
It is suggested that research and development be done of a new method for automated processing of electrocardiograms (ECG) and based on it innovative digital cardio-analyzer intended for differential diagnosis of acute myocardial infarction (AMI) and other heart diseases.
This cardio analyzer is expected to have the following automated functions:
- effective diagnostics (with non-contradictory conclusions) of AMI of different locations at different phases of the disease;
- contour analysis of the ECG signal providing a description of the ECG elements in natural language and distinguishing qualitative diagnostic features of ECG curve variation for different diseases;
- making a conclusion on ECG evolution by comparison of ECGs taken at different time moments and stored in the specialized database;
- interactive training for the students of medical higher schools and universities including capability of demonstrating indicatory and reciprocal features of ECG shape variations.
Unlike well-known digital cardiographs, the proposed cardio-analyzer will give a complete description of ECG curve in a natural language (e.g. Russian or English), thus requiring no decoding explanations from physicians, saving their time.
This would be possible due to the application of the innovative techniques of processing functional curves and potential surfaces. It should be noted that the problems under study can be referred to a class of non-stationary problems with inaccurate data. This means that it is unfeasible to obtain full information about the processes taking place in the object under study. Therefore, a part of the signal curve which is reproduced several times during ECG-taking period is the most stable and significant in terms of diagnostics. In some cases data of conventional digital cardiographs based on the analysis of interval-amplitude parameters of the ECG components do not allow generation of credible conclusions.
A technique to be developed for formal description of the digital curves will be based on automated construction of a specialized graph-like structure enveloping an arbitrary functional curve (including ECG). The elements of this structure will be then used to establish a system of predicative formulas for recognition of the functional curve (ECG) elements. Configurations of specific sub-graphs will correspond to some specific elements, their relative positions and the functional curve configuration, as a whole. Thus, analyzing the components of the graph-like structure will make it possible to refer the curve under study to one of the set of classes and identify an appropriate disease.
An original code for ECG description will be developed which will differ from the conventional ones and will implement a set of rules for distinguishing diagnostics of AMI and its complications.
A set of rules will be developed to analyze ECG dynamics by comparing patient-specific ECGs stored in the specialized database and to recommend a proper correction of diagnostic conclusion.
It is planned to develop a friendly user’s interface, perse forms of presenting interim and final data of ECG analysis, a fast search for the information needed, an effective archive maintenance and other services.
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