##plugins.themes.bootstrap3.article.main##

The results of examination of the condition of the heart using an electrocardiograph are generally presented in an ecg paper. Using ecg paper because in the paper there are boxes that are used as guidelines for calculating wave amplitude and wave duration. If the required amplitude is information on peak amplitude and wave morphology information, then the duration is information on the value of segment duration, interval duration, and heart rate. As is known in the ECG paper the results of the examination that only some information is presented, so information that does not yet exist must be calculated manually using existing boxes. This manual calculation requires time and accuracy, so that this waiting time can cause the patient's disease stage to increase, and on the other hand that the lack of accuracy of the calculation can cause misdiagnosis. This study aims to provide information on clinical standard cardiac examination results using Electrocardiograph discrete (ECGd) and standard Electrocardiograph (ECGs). In ECGd, the leads of the heart signal are sampled at a frequency of 250 Hz so that it becomes discrete data. Maximum filtering on 1.6 mV treshold data discrete peak R is obtained in each cycle. The PQRST algorithm method is used to get the PQST peak and duration parameters. The results showed that the percentage of the amount of information from the ECGd examination was 82.4% while the results of the ECGs examination were 25.4%

Downloads

Download data is not yet available.

References

  1. A. C. Guyton and J. E. Hall, Textbook of Medical Physiology, 11th ed. Mississippi: Elsevier Saundes, 2006.
     Google Scholar
  2. J. R. Cameron and J. G. Skofronick, Medical physics. Wiley, 1978.
     Google Scholar
  3. D. B. Foster, Twelve-Lead Electrocardiography, Second. London: Springer-Verlag London, 2007.
     Google Scholar
  4. P. A. Iaizzo, Handbook of Cardiac Anatomy, Physiology, and Devices, ANSI Z39.48-1984 (American National Standards Institute) Permanence of Paper for Printed Library Materials. Totowa, New Jersey 07512: ? 2005 Humana Press Inc., 2005.
     Google Scholar
  5. R. H. John, The ECG in Practice, Fourth Edition. Notingham UK: Churchill Livingstone An imprint of Elsevier Science Limited, 2003.
     Google Scholar
  6. B. Chia, Cninical Electrocardiography, Third Edition. New Jersey: World Scientific, 2000.
     Google Scholar
  7. kartika Bawa and P. Sabherwal, ?R-Peak Detection by Modified Pan-Tompkins Algorithm | IJOART Editor - Academia.edu,? 2014. [Online]. Available: https://www.academia.edu/8224161/R-Peak_Detection_by_Modified_Pan-Tompkins_Algorithm. [Accessed: 06-Jun-2017].
     Google Scholar
  8. G. D. Clifford, F. Azuaje, and P. E. McSharry, Advanced Methods and Tools for ECG Data Analysis, First Edition. Boston, London: 2006 ARTECH HOUSE, INC. 685 Canton Street Norwood, MA 02062, 2006.
     Google Scholar
  9. A. Natale, A. Al-Ahmad, P. J. Wang, and J. DiMarco, Cardiac Electrophysiology. London: Springer London Dordrecht Heidelberg New York, 2011.
     Google Scholar
  10. A. Tariq Bhatti and J. H. Kim, ?R-Peak detection in ECG signal compression for Heartbeat rate patients at 1KHz using High Order Statistic Algorithm,? J. Multidiscip. Eng. Sci. Technol. JMEST, vol. Vol. 2, no. Issue 9, pp. 7 (2509-2515), Sep. 2015.
     Google Scholar
  11. A. Birle, S. Malviya, and D. Mittal, ?A Novel Technique of R - Peak Detecti on for ECG Signal Analysis: Variable Threshold Method,? Int. J. Adv. Res. Electron. Commun. Eng. IJARECE, vol. 4, no. 5, pp. 3 (1167-1169), May 2015.
     Google Scholar
  12. H. A. Jaber AL-Ziarjawey and I. Cankaya, ?Heart Rate Monitoring and PQRST Detection Based on Graphical user Interface with Matlab,? Int. J. Inf. Electron. Eng., vol. 5, No.4, p. 6, Jul. 2015.
     Google Scholar
  13. J. Sharma, V. Kumar, S. Ayub, and J. P. Saini, ?Uniform Sampling of ECG Waveform of MIT-BIH Normal Sinus Rhythm Database at Desired Intervals,? Int. J. Comput. Appl., vol. 50, No.15, pp. 4 (6-9), Jul. 2012.
     Google Scholar
  14. Er. J. S. Dhir and Er. N. K. Panag, ?ECG Analysis and R Peak Detection Using Filters and Wavelet Transform,? Int. J. Innov. Res. Comput. Commun. Eng. IJIRCCE, vol. 2, no. 2, pp. 8 (2883-2890), Feb. 2014.
     Google Scholar
  15. L. K. Wee, Y. K. Jiar, and E. Supriyanto, ?Electrocardiogram Data Capturing System and Computerized Digitization using Image Processing Techniques,? Int. J. Biol. Biomed. Eng., vol. 3, no. 3, pp. 8 (27-34), 2009.
     Google Scholar
  16. M. Schmidt, J. W. Krug, A. Gierstorfer, and G. Rose, ?A real-time QRS detector based on higher-order statistics for ECG gated cardiac MRI,? Comput. Cardiol. 2014, pp. 3 (733-736), 2014.
     Google Scholar
  17. M. Talbi, A. Aouinet, L. Salhi, and A. Cherif, ?New Method of R-Wave Detection by Continuous Wavelet Transform,? Signal Process. Int. J. SPIJ, vol. 5, no. 4, pp. 9 (165-173), 2011.
     Google Scholar
  18. I. S. S. Rao, T. S. Rao, and P. H. S. T. Murthy, ?QRS Detection of ECG - A Statistical Analysis,? ICTACT J. Commun. Technol., vol. 06, no. 01, pp. 4 (1080-1083), Mar. 2015.
     Google Scholar
  19. D. Sadhukhan and M. Mitra, ?R-peak detection algorithm for ECG using double difference and RR interval processing,? Elsevier Procedia Technol., vol. 4, pp. 5 (873-877), 2012.
     Google Scholar
  20. S. singh and N. Gandhi.N, ?Pattern analysis of different ECG signal using Pan-Tompkin?s algorithm,? Int. J. Comput. Sci. Eng. IJCSE, vol. 02, No. 07, pp. 4 (2502-2505), 2010.
     Google Scholar
  21. D. Sadhukhan and M. Mitra, ?R-peak detection algorithm for ECG using double difference and RR interval processing,? Procedia Technol. Elsevier Ltd Open Access, vol. 4, p. 5, 2012, doi: 10.1016/j.protcy.2012.05.143.
     Google Scholar
  22. J. Sharma, V. Kumar, S. Ayub, and J. P. Saini, ?Uniform Sampling of ECG Waveform of MIT-BIH Normal Sinus Rhythm Database at Desired Intervals,? Int. J. Comput. Appl., vol. 50, no. 15, pp. 6?9, Jul. 2012, doi: 10.5120/7845-0912.
     Google Scholar
  23. M. Singh, B. Singh, and V. Banga, ?Effect of ECG Sampling Frequency on Approximate Entropy based HRV,? ResearchGate, Aug-2014. [Online]. Available: https://www.researchgate.net/publication/284466918_Effect_of_ECG_Sampling_Frequency_on_Approximate_Entropy_based_HRV. [Accessed: 07-Jun-2017].
     Google Scholar
  24. S. Setiawidayat and R. Joegijantoro, ?Algorithm for the Representation of Parameter Values of Electrocardiogram,? Telkomnika, vol. Vol.16, no.3, no. Medical Engineering, p. 8, Jun. 2018, doi: DOI: 10.12928/TELKOMNIKA.v16i3.6934.
     Google Scholar
  25. S. Setiawidayat, R. Indra, D. Sargowo, and S. P. Sakti, ?Determining The ECG 1 Cycle wave Using Discrete Data,? J. Theor. Appl. Inf. Technol., vol. 88, No.1, pp. 8 (107-114), Jun. 2016.
     Google Scholar
  26. B. Chia, Clinical Electrocardiography, Third Edition. Singapura: World Scientific Publishing Co. Re. Ltd.Singapura, 2000.
     Google Scholar