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Identification of Premature Ventricular Contraction ECG Signal using Wavelet Detection

by I Dewa Gede Hari Wisana, Thomas Sri Widodo, Mochammad Sja’bani, Adhi Susanto
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 16
Year of Publication: 2012
Authors: I Dewa Gede Hari Wisana, Thomas Sri Widodo, Mochammad Sja’bani, Adhi Susanto
10.5120/6992-9424

I Dewa Gede Hari Wisana, Thomas Sri Widodo, Mochammad Sja’bani, Adhi Susanto . Identification of Premature Ventricular Contraction ECG Signal using Wavelet Detection. International Journal of Computer Applications. 46, 16 ( May 2012), 11-15. DOI=10.5120/6992-9424

@article{ 10.5120/6992-9424,
author = { I Dewa Gede Hari Wisana, Thomas Sri Widodo, Mochammad Sja’bani, Adhi Susanto },
title = { Identification of Premature Ventricular Contraction ECG Signal using Wavelet Detection },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 16 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number16/6992-9424/ },
doi = { 10.5120/6992-9424 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:39:53.756708+05:30
%A I Dewa Gede Hari Wisana
%A Thomas Sri Widodo
%A Mochammad Sja’bani
%A Adhi Susanto
%T Identification of Premature Ventricular Contraction ECG Signal using Wavelet Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 16
%P 11-15
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the wavelet method used for detecting an electrocardiogram signal is the detection of a new wavelet. Specific form of the electrocardiogram signal which gives angle, amplitude, phase and certain frequency is used as the basis of new wavelet formation. Algorithm DeGePVC is a new algorithm to detect Premature Ventricular Contraction wave electrocardiogram signal. The advantage of using this algorithm DeGePVC is reducing the sensitivity to noise compared to other techniques, with the determination of each component of P, Q, R, S, T wave of the electrocardiogram accurately and quickly. The originality of this study was applied to Premature Ventricular Contraction electrocardiogram wave, with varying leads and it is analyzed for each component of its electrocardiogram signal. The results show the effectiveness of DeGePVC wavelet algorithm utility to detect Premature Ventricular Contraction electrocardiogram wave for 6 lead electrocardiogram. With the value of auc=0. 988 by using Receiver Operating Charactheristic (ROC) curve.

References
  1. Addison P S, Watson J N, 2003,Evaluating arrhythmias in ECGsignals using wavelet transforms,IEEE Eng Med Biol,Vol. 19, pp. 104–9.
  2. Addison P S, Watson J N, Clegg G R, 2005, Finding coordinated atrial activity duringventricular fibrillation using wavelet decomposition,IEEE Eng. Med. Biol, Vol. 21, pp. 58–65.
  3. Amara Grap, 2005, An Introduction to wavelet, IEEE Trans. Comp. Sc. And Eng, Vol. 2, No. 2.
  4. Bradie,2001, Wavelet packet-based compression of single lead ECG,IEEE Trans. Biomed. Eng. Vol. 43, pp. 493–501.
  5. Burrus, C. S. ,R. A. Gopinath, H. Guo, 2004, Introduction to wavelet and wavelet transforms, A PRIMER. Upper Saddle River, NJ Prentice Hall.
  6. Calderbank, Daubechies, Sweldens, Yeo, 1996, Wavelet transforms that map integers to integers. Proceedings of the IEEE Conference on Image Processing. Preprint,IEEE Press.
  7. Carmona R A, Hwang, Torresani , 1997,Characterization of signals by the ridges of their wavelet transform , IEEE Trans Signal Process,Vol. 45, pp. 2586–90.
  8. Chen Sw, 2002,A wavelet-based heart-rate variability analysis for the study of nonsustained ventricular tachycardia,IEEE Trans Biomed Eng,Vol. 49, pp. 736–42.
  9. Daubechies, I, 1999, Ten lectures on wavelet. Philadelphia SIAMCBMSNSF. regional conference series in applied mathematics 61.
  10. Daubechies, 2001, The wavelet Transform, Time-Frequency Localization and Signal Analysis, IEEE Trans Inform Theory, pp. 961–1005.
  11. Delprat N, Escudie B, Guillemain P,1992,Asymptotic waveletand Gabor analysis: extraction of instantaneous frequencies,IEEE Trans Inf Theory, Vol. 38, No. 644–64.
  12. Fischer,Akay ,2003, Fractal analysis of heart rate variability Time Frequency and Wavelets in BiomedicalSignal Processing, IEEE, chapter 7 pp 719–28
  13. Gary F, Thomas, ManalAfidyJadallah, 2001, A Comparison of the noise sensitivity of nine QRS detection algorithms, IEEE Transaction of Biomedical Engineering, Vol. 37, No. 1.
  14. Goldberger, Amaral , 2000, PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation101(23):e215-e220 Circulation Electronic Pages; http://circ. ahajournals. org/cgi/content/full/101/23/e215.
  15. John Darrington, 2009, Towards real time QRS detection: A fast method using minimal pre-processing, Biomedical Signal Processing and Control.
  16. Körner, T. W, 2001, Fourier analysis , Cambridge University Press, Cambridge UK.
  17. Kohler B U, Hennig C, 2002,The principles of software QRS detection,IEEE Eng. Med. Biol,Vol. 21, pp. 42–57.
  18. Lemire D, Pharand C, Rajaonah, 2000,Wavelet time entropy T wave morphology andmyocardial ischemia, IEEE Trans Biomed Eng, Vol. 47, pp. 967–70.
  19. Li, Zheng C, Tai C, 2000, Detection of EKG characteristic points using wavelet transform, IEEE, Transaction on biomedical engineering, Vol. 42, No. 21-28.
  20. Lloyd W, Klein, Sandeep Nathan, 2003, Coronary artery diseases in young adulths, Journal of the American College of Cardiology Foundation.
  21. Maclachan, 2006, Size and location of Myocardial Ischemia using Measurements of ST- segment shift, IEEE Transaction of Biomedical Engineering, Vol. 53, No. 6.
  22. Mallat, S. G, 2002, A theory for multiresolution signal decomposition: the waveletrepresentation, IEEE Transactions on Pattern Analysis and Machine Intelligence.
  23. Ruha, Sallinen, 2000, A real-time microprocessor QRSdetector system with 1-ms timing accuracy for the measurement of ambulatory HRV, IEEE Trans Biomed Eng, Vol. 44, pp. 159–167.
  24. Sahambi J S, Tandon S M, Bhatt, 1997,Using wavelet transforms for ECG characterization: an on-linedigital signal processing system, IEEE Eng Med Biol,Vol. 16, pp. 77–83.
  25. Senhadji L, Carrault G, 2000,Comparing wavelet transforms for recognizing cardiacpatterns,IEEE Trans Med Biol, Vol. 13, pp. 167–73.
  26. Sheng. Y, 1998, wavelet transform. in: the transforms and applications handbook, the Electrical Engineering Handbook Series.
  27. Shirley Jones, 2005, ECG Notes: Interpretation and Management Guide, F. A Davis company, Philadelphia.
  28. Vetterli M. and C. Herley, 2001, wavelet and filter banks: theory and design, IEEE Transactions on Signal Processing.
Index Terms

Computer Science
Information Sciences

Keywords

Degepvc Electrordiogram Wavelet Detection Premature Ventricular Contraction.

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