Home > tuitmct > Vol. 1 (2018)

## Bulletin of TUIT: Management and Communication Technologies

#### Article Title

#### Abstract

The article discusses the use of wavelet transforms and algorithms in the digital processing of cardiosignals in a number of medical applications due to their good adaptability to the analysis of non-stationary signals (that is, those whose statistical characteristics change with time). Since an electrocardiogram is a transient signal, wavelet methods can be used to recognize and detect key diagnostic features. In real-time systems for digital signal processing, it is important that mathematical operations are performed quickly, and the time required to execute commands must be known precisely and in advance. For this, both the program and the hardware must be very effective. In digital signal processors, the most important mathematical operation and the core of all digital signal processing algorithms is multiplication, followed by summation. Fast execution of the multiplication operation followed by summation is very important for implementing real-time digital filters, signal processing, matrix multiplication, and graphic image manipulation. Therefore, all this requires the need to improve methods, algorithms and signal processing programs that determine the quality and performance of digital systems. The technique is based on the transformation of the heart rate to simple harmonic oscillations (fast Fourier transform, autoregressive analysis) with different frequencies. In this case, the sequence of heartbeats is converted into a power spectrum of fluctuations of the duration of the RR intervals, which are a sequence of frequencies characterizing HRV. Most often, the area bounded by the spectral power curve corresponding to a certain defined frequency range, that is, the power within a limited frequency range, is estimated.

#### First Page

15

#### Last Page

20

#### References

[1] Smolentsev N. K. Osnovi teorii veyvletov. Veyvleti v MATLAB / Smolentsev N. K. - M. : DMK Press, 2008. - 448 s. [2] H.N.Zaynidinov, M.B.Zaynutdinova, E.Sh.Nazirova. Methods of reconstructing signals based on multivariate spline. European journal of computer science and information technology, Vol.3, No.2, pp.52-59, May 2015, ISSN 2054-0957(Print), ISSN 2054-0965 (On-line). [3] H.N.Zaynidinov, M.B.Zaynutdinova, S.U.Makhmudjanov. Multiprocessor parallel pipelined computation structure on the basis of bicubic splines. WCIS-2016 “Ninth World Conference on Intelligent Systems for Industrial Automation”. PROCEEDINGS, Tashkent, Uzbekistan, October25-27, 2016, p.166-170 [4] H.N.Zaynidinov, M.B.Zaynutdinova, I.Yusupov.Two-dimensional piecewise-polynomial haar’s bases and their application to problems in digital signal processing. WCIS-2016 “Ninth World Conference on Intelligent Systems for Industrial Automation”. PROCEEDINGS, Tashkent, Uzbekistan, October25-27, 2016, p.371-376 [5] X.N.Zayniddinov, I.Yusupov. Piecewise-polynomial basis functions for com-puting problems in biomedical signal processing. ABSTRACTS of the Uzbek – Israel International Scientific Conference “CONTEMPORARY PROBLEMS IN MATHEMATICS AND PHYSICS” Tashkent 2017 October 6-10, 127 p. [6] Xan M. G. Bistriy analiz EKG / M. G. Xan. - M. :Bi¬nom, 2003. – 230 s. [7] Xempton Dj. Atlas EKG: 150 klinicheskix situatsiy / Dj. Xempton. - M. : Meditsinskaya literatura, 2007. - 320 s. [8] Smolentsev N. K. Osnovi teorii veyvletov. Veyvleti v MATLAB / Smolentsev N. K. - M. : DMK Press, 2008. - 448 s. [9] Alekseev K. A. Ocherk «Vokrug CWT» [Elektronniy resurs] / Alekseev K. A. - Elektron.dan. - Rejim dostupu: http://matlab.exponenta.ru/wavelet/ book3/in- dex.php, vshьniy. - Zag. zekranu. [10] Martinez J. P. A wavelet-based ECG delineator: evaluati¬on on standard databases / Martinez J. P., Almeida R., La¬guna P. // IEEE Transactions on Biomedical Engineering. - 2004. - Vol. 51. - P. 570-581 [11] Vitec M. A wavelet-based ECG delineation in Multilead ECG signals: Evaluation on the CSE Database / Vitec M., Hrubes J., Kozumplik J. // IFMBE Proceedings. - 2009. - Vol.25. - P. 177-180 [12] Sahambi J. S. Using wavelet transform for ECG characteri¬zation / Sahambi J. S., Tandon S. B. // IEEE Engineering in Medicine and Biology. - 2000. - Vol. 9. - P. 1532-1546 [13] Chouhan V. S. Delineation of QRS-complex, P and T-wa- ve in 12-lead ECG / Chouhan V S., Mehta S. S., LingayatN. S. // IJCSNS International Journal of Compu¬ter Science and Network Security. - 2008. - Vol. 8. - P. 185-190 [14] De Chazazl P. Automatic measurement of the QRS onset and offset in individual ECG leads / De Chazazl P., Celler B. // IEEE Engineering in Medicine and Biology Society. - 1996. - Vol. 4. - P. 1399-1403 [15] Laguna P. Automatic detection of wave boundaries in multilead ECG signals / Laguna P., Jane R., Caminal P. // Computers and Biomedical Research. - 1994. - Vol. 27. - P. 45-60. [16] Dohoto D. L. De-Noising by soft-thresholding / Do- hoto D. L. // IEEE Transactions on Information Theory. - 2005. - Vol. 41. - P. 613-627. [17] Dohoto D. L. Ideal spatial adaptation via wavelet shrinka¬ge / Dohoto D. L., Johnstone I. M. // Biometrika. - 2004. - Vol. 81. - P. 425-455. [18] H. Zaynidinov, U. Khamdamov. Parallel Algorithms for Bitmap Image Processing Based on Daubechies Wavelets. 10th International Conference on Communication Software and Networks (Indexed by SCOPUS). July 6-9, 2018, Chengdu, China. [19] Dhananjay Singh, Madhusudan Singh, Hakimjon Zaynidinov "Signal Processing Applications Using Multidimensional Polynomial Splines", (Monografiya na angliyskom yazike), Springer Briefs in Applied Sciences and Technology Series, Springer, Singapore, (Indexed by EI-Compendex, SCOPUS and Springerlink, 2019,70 p. [20] H. N. Zayniddinov, Madhusudan Singh, Dhananjay Singh. Polynomial Splines for Digital Signal and Systems. LAMBERT Academic publishing, Germany, 2016 year, 208 p.

#### Recommended Citation

Zaynidinov, Hakimjon Nasridinovich prof.; Zaynutdinova, Dilfuza Bahodirovna dos.; Azimova, Umida; and Kuchkarov, Muslim Adhamovich
(2018)
"WAVELET METHODS FOR CARDIO SIGNALS PROCESSING,"
*Bulletin of TUIT: Management and Communication Technologies*: Vol. 1
, Article 3.

Available at:
https://uzjournals.edu.uz/tuitmct/vol1/iss2/3