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Известия высших учебных заведений России. Радиоэлектроника

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Systematic Approach to Processing and Analysis Diagnostic Indicators of Electrocardiograms Based on Labview

https://doi.org/10.32603/1993-8985-2020-23-2-82-88

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Аннотация

Introduction. Cardiovascular disease occupies an important place throughout the world, which necessitates the development of more effective modern means of diagnosis and treatment. The primary diagnosis of heart disease is based on analysis and processing of an electrocardiogram (ECG). Despite the fact that there are many methods and algorithms for ECG analysis and processing, one of the urgent problems of cardiology remains to obtain the most complete information about heart electric potential, respectively, the behavior of the waves P, Q, R, S and T.

Aim. Development of algorithms and software for processing and analysis of electrocardiograms (ECGs), as well as calculation of heart rate and detection of arrhythmias based on Labview.

Materials and methods. The methods for removing noise using the wavelet transform method to eliminate baseline deviation ,to extract ECG signs ,to calculate heart rate and to detect arrhythmias based on Labview have been adopted as a mathematical apparatus for processing and analyzing ECGs.

Results. Organizing of the ECG database, developing algorithms for converting the ECG file of the database into a useful format for Labview, processing of the ECG signal with removing noise from the original ECG signal, extracting signs for obtaining ECG diagnostic indicators, calculating heart rate and detecting arrhythmias.

Conclusion. An analysis of the results demonstrates that systematic approaches to evaluating ECG signals allow to avoid one-way decisions and to integrate different methods into an integrated system of ideas of the state. The implementation of the proposed algorithms using Labview programming system ensures the removal of noise and artifacts, the extraction of the necessary ECG signs, the calculation of heart contractions and the detection of arrhythmias.

Об авторах

M. T. Magrupova
Tashkent State Technical University
Узбекистан
Malokhat T. Magrupova, PhD student, senior lecturer at the Department of Metrology, Standardization and Certification in the named university. The author of more than 20 scientific publications. Area expertise: metrological assurance of the reliability of medical and biological objects.


Yo. T. Talatov
Tashkent State Technical University
Узбекистан

Yokubjon T. Talatov, Master in Biomedical Engineering (2015), PhD student in Biomedical Engineering

The author of more than 15 scientific publications. Area expertise: algorithmic and software analysis and processing ‒ biomedical information. 



Список литературы

1. Magrupov T. M., Vasil'eva S. A., Magrupova M. T. Analiz i obrabotka medico-biologicheskoi informatsii [Analysis and processing of biomedical information]. Toshkent, TashGTU, 2012. 152 p. (In Russ.)

2. Rangayyan R. M. Biomedical Signal Analysis. 2nd Ed. Wiley-IEEE Press, 2015. 720 p.

3. Baevskii R. M., Ivanov G. G., Chireiki, L. V., Gavrilushkin A. P., Dovgalevskii P. Ya., Kukushkin Yu. A., Mironova T. F., Prilutskii D. A., Semenov A. V., Fedorov V. F., Fleishman A. N., Medvedev M. M. Methodical Recommendations: Analysis of Heart Rate Variability when Using Various Electrocardiographic Systems. Journal of Arrhythmology. 2001, no. 24, pp. 65–87. (In Russ.)

4. Malik M. Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation. 1996, vol. 93, iss. 5, pp. 1043–1065.

5. Schuster H. G., Just W. Deterministic Chaos: An Introduction. 4th Ed. Wiley-VCH Verlag, 2005, 287 p. doi: 10.1002/3527604804

6. Ardashev A.V., Loskutov A. Yu. Prakticheskie aspekty sovremennykh metodov analiza variabel'nosti serdechnogo ritma [Practical Aspects of Modern Methods of Analyzing Heart Rate Variability]. Moscow, ID MEDPRAKTIKA-M, 2011, 128 p. (In Russ.)

7. Fleishman A. N. Heart Rate Variability and Slow Hemodynamic Fluctuations. Nonlinear Phenomena in Clinical Practice. Novokuznetsk, 2009, 185 p. (In Russ.)

8. Fabian J. T., Anke M.-B. Biomedical Signal Analysis: Contemporary Methods and Applications. Cambridge, MA, MIT Press, 2010, 432 p.

9. Islam M. K., Haque A. N. M. M., Tangim G., Ahammad T., Khondokar M. R. H. Study and Analysis of ECG Signal Using Matlab Labview as Effective Tools. Intern. J. of Computer and Electrical Engineering. 2012, vol. 4, no. 3, pp. 404‒408. doi: 10.7763/IJCEE.2012.V4.522

10. German-Sallo Z. ECG Signal Baseline Wander Removal Using Wavelet Analysis. Intern. Conf. on Advancements of Medicine and Health Care through Technology. 2011, vol. 36, pp. 190‒193. doi: 10.1007/978-3-642-22586-4_41

11. Haque A. K. M. F., Ali H., Kiber M. A., Hasan Md. T. Detection of Small Variations of ECG Features Using Wavelet. J. of Engineering and Applied Sciences. 2009, vol. 4, no. 6, pp. 27‒30,

12. Lin Y. D., Hu Y. H. Power-Line Interference Detection and Suppression in ECG Signal Processing. IEEE Transactions on Biomedical Engineering. 2008, vol. 55, no. 1, pp. 354‒357. doi: 10.1109/TBME.2007.902234

13. German-Sallo Z. ECG Signal Baseline Wander Removal Using Wavelet Analysis. Intern. Conf. on Advancements of Medicine and Health Care through Technology. 2011, vol. 36, pp. 190‒193.

14. Saritha C., Sukanya V., Murthy Y. N. ECG Signal Analysis Using Wavelet Transforms. Bulg. J. Phys. 2008, vol. 35, pp. 68– 77.

15. Talatov Y. T., Magrupova M. T. Generalization of Processing of Electrocardiograms and Calculation of Heart Rate. Digital Region: Experience, Competencies, Projects: Collection of Articles of the International Scientific and Practical Conference. Bryansk, Russia, 19 November, 2019. Bryansk, Bryan. State Engineering Technol. Univ., 2019, 670‒675 p. (In Russ.)

16. Talatov Y., Magrupov T., Radjabov A. A Device for Measuring of Frequency. SIBIRCON 2019. Proc. of Intern. Multi-Conf. on Engineering, Computer and Information Sciences. Novosibirsk, Russia, 21-27 Oct. 2019. Piscataway, IEEE, 2019. doi: 10.1109/SIBIRCON48586.2019.8958401

17. Talatov Y., Magrupov T. Algorithmic and Software Analysis and Processing of ECG Signals. SIBIRCON 2019. Proc. of Intern. Multi-Conf. on Engineering, Computer and Information Sciences. Novosibirsk, Russia, 21‒27 Oct. 2019. Piscataway, IEEE, 2019. doi: 10.1109/SIBIRCON48586.2019.8958424


Для цитирования:


Magrupova M.T., Talatov Y.T. Systematic Approach to Processing and Analysis Diagnostic Indicators of Electrocardiograms Based on Labview. Известия высших учебных заведений России. Радиоэлектроника. 2020;23(2):82-88. https://doi.org/10.32603/1993-8985-2020-23-2-82-88

For citation:


Magrupova M.T., Talatov Y.T. Systematic Approach to Processing and Analysis Diagnostic Indicators of Electrocardiograms Based on Labview. Journal of the Russian Universities. Radioelectronics. 2020;23(2):82-88. https://doi.org/10.32603/1993-8985-2020-23-2-82-88

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ISSN 1993-8985 (Print)
ISSN 2658-4794 (Online)