FORMATION AND ANALYSIS OF ECG SIGNALS WITH PATHOLOGIES
Keywords:electrocardiogram, pathology, infarction, QRS-complex, wavelet transform
AbstractContext. The work is devoted to the actual problem of the generation of electrocardiogram signals with distortions corresponding to the
different pathologies. These signals can be used as a standard for developing new and verification of existing methods for biomedical signals analyzing aimed at the diagnosis of heart diseases.
Objective. The aim of this work is the formation of electrocardiogram signals with the known types of distortions corresponding to the
common pathologies. The formation of electrocardiogram signals with pathologies is carried out in accordance with heart disease «myocardial
infarction» as it is the most widespread among all the heart diseases which can be lethal.
Method. The description of a set of diagnostic disease symptoms for elements of electrocardiogram signal depending on the type of
infarction (subendocardial or transmural) and its stage is studied. To generate the electrocardiogram signals with the given pathologies the
modeling using an offset, shift, scale or exception in the time domain of allocated signal component of the normal electrocardiogram is
conducted. The time-frequency analysis methods (continuous wavelet transform with the maternal function «Mexican hat» and wavelet
transform with the wavelet function «bior1.5») are used for electrocardiogram component detection and determination of their parameters.
Results. It came possible to generate electrocardiogram signals both without and with pathologies in the forms of subendocardial and
transmural myocardial infarction. Based on the time-frequency analysis of the obtained electrocardiograms it came possible to determine the
features of artificially generated signals corresponding to the pledged pathologies.
Conclusions (scientific novelty and practical significance). The problem of synthetic formation of an electrocardiogram signal
containing deviations from the norm in accordance with the pathologies «subendocardial infarction» and «transmural infarction» is resolved.
As a result of the subsequent studies of the received signals with pathologies the method of analysis of electrocardiograms based on wavelet transform is further developed. Recommendations for the use of this method to detect the pathologies in the forms of subendocardial and transmural myocardial infarctions are given. The results of this work are planed to be used in the future to develop electrocardiograms analysis methods for early detection of known cardiac pathologies.
Рангайян Р. М. Анализ биомедицинских сигналов. Практический подход / Р. М. Рангайян. – М. : Физматлит, 2007. – 440 с. 2. Чесноков Ю. В. Вейвлет-преобразование в обработке электрокардиограмм / Ю. В. Чесноков, В. И. Чижиков // Вестник новых медицинских технологий. – 2003. – Т. X, № 1.– С. 5–8. 3. Хафизов А. Р. Использование вейвлет-преобразования при анализе ЭКГ / А. Р. Хафизов, М. В. Башашин // Издание МИФИ. – 1999. – Т. 7. – С. 16–17. 4. Брюханов Ю. А. Основы цифровой обработки сигналов / Ю. А. Брюханов, А. Л. Приоров. – Ярославль : ЯрГУ, 2013. – 344 с. 5. Vitec M. A Wavelet-Based ECG Delineation with Improved P Wave Offset Detection Accuracy / M. Vitec, J. Hrubes // Analysis of Biomedical Signals and Images. – 2010. – P. 160–165. 6. Vitec M. A wavelet-based ECG delineation in Multilead ECG signals:Evaluation on the CSE Database / M. Vitec, J. Hrubes // IFMBE Proceedings. – 2009. – Vol. 25. – P. 177–180. 7. Mart nez J. P. A wavelet-based ECG delineator: evaluation on standard databases / [J. P. Martí nez, R. Almeida, S. Olmos and other ] // IEEE Transactions on Biomedical Engineering. – 2004. – Vol. 51, No. 4. – P. 570–581. 8. Sahambi J. S. Using wavelet transform for ECG characterization / J. S. Sahambi, S. Tandon, R.K.P. Bhatt // IEEE Engineering in Medicine and Biology. – 1997. – Vol. 16, No. 1. – P. 77–83. 9. Дубровин В. И. Усовершенствование методов анализа ЭКГ-сигналов на основе вейвлет-преобразования в системе электрокардиографии высокого разрешения / В. И. Дубровин, Ю. В. Твердохлеб // Радіоелектроніка, інформатика, управлін- ня. – 2011. – № 1. – С. 91–98.
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