NI LabVIEW kullanarak EKG sinyallerinin gerçek zamanlı özellik çıkarımı

Year 2017, , 576 - 583, 01.08.2017

Ayşe Nur Ay Mustafa Zahid Yıldız , Barış Boru

https://doi.org/10.16984/saufenbilder.287418

Cited By: 2

Abstract

Bu proje, NI LabVIEW programı sayesinde insan
vücudundan gerçek zamanlı elektrokardiyogram (EKG) ölçümüne dayanır.Sadece ham
sinyaller değil, programın filtreleme toolları sayesinde dijital filtrelenmiş
EKG de gerçek zamanlı görülebilir. EKG sinyalinin kendisi birçok diagnostik
bilgi içerir. NI LabVIEW biomedical toolkit, biyomedikal sinyalleri işleme ve
özellik çıkarımı için birçok tool barındırır. Bu nedenle, EKG verilerini almak
için bu program tercih edilmiştir. Bu çalışmada, EKG sinyali üzerinden R-R
dalgaları tespit edilerek hastaların kalp atış hızı Teager enerji metodu ile
hesaplanmıştır. Bu sistemi test etmek için 12 kişi üzerinde birtakım deneyler
yapılmıştır (6 sigara içmeyen + 6 sigara içen). Deneye katılan insanlarin
dinlenme halindeki ve koştuktan sonraki EKG dataları ölçülmüştür. Bu deneylerin
sonuçları grafiksel ve istatistiksel analizler için kaydedilmiştir. Bu sonuçlara
göre sigara içmenin kalp atış hızına etkisi tartışılmıştır.

Keywords

Elektrokardiyogram, Özellik Çıkarımı, NI LabVIEW

Real-time feature extraction of ECG signals using NI LabVIEW

Abstract

This study is based on measuring the
Electrocardiogram (ECG) signals from the human body in real-time with the help
of the software called NI LabVIEW. Not only the raw ECG signals, the digital
filtered version of the ECG signals can also be displayed in real-time by
processing the signals using the digital filtering tools of the program. The
ECG itself provides various diagnostic information and NI LabVIEW biomedical
toolkit offers many tools that helps to process the signals and perform
feature extraction. Thus, this software was preferred for the ECG data acquisition.
In this project, heart rate of a patient is calculated by detecting R-R
intervals on the ECG tracing using the method called Teager Energy. In order
to test the system, several experiments have been conducted with 12 subjects
(6 non-smokers + 6 smokers). Their ECG signals were taken in relaxed and after
running conditions. The experimental results were recorded for the graphical
and statistical analysis. According to the results, the effect of smoking to
the heart rate was discussed.

Keywords

ECG, LabVIEW, Medical Instrumentation

References

• [1] C.Saritha, V.Sukanya and Y.Narasimha Murthy, "ECG signal analysis using wavelet transforms," Bulgarian Journal of Physics, vol. 35, pp. 68-77, 2008.
• [2] A. Fratini, M. Sansone, P. Bifulco and M. Cesarelli, "Individual identification via electrocardiogram analysis," Biomedical Engineering Online, no. DOI 10.1186/s12938-015-0072-y, 2015.
• [3] M. K. Islam, A. N. M. M. Haque, G. Tangim, T. Ahammad and M. R. H. Khondokar, "Study and Analysis of ECG Signal Using MATLAB & LABVIEW as Effective Tools," International Journal of Computer and Electrical Engineering, vol. 4, no. 3, June 2012.
• [4] M. Babu, R. R. Raju, S. Sylevester, T. M. Mathew and K. M. Abubeker, "Real Time Patient Monitoring System Using LabVIEW," International Journal of Advanced Research in Computer and Communication Engineering, vol. 5, no. 3, 2016.
• [5] S. Gupta and J. John, "Virtual Instrumentation Using LabVIEW," in Principle and Practices of Gaphical Programming, 2nd ed., New Delhi, Tata McGraw Hill, 2010.
• [6] A. Kumar, L. Dewan and M. SINGH, "Real Time Monitoring System for ECG Signal Using Virtual Instrumentation," WSEAS TRANSACTIONS on BIOLOGY and BIOMEDICINE, vol. 3, no. 11, 2006.
• [7] User Guide NI myDAQ, National Instruments Company, 2014.
• [8] J. G. Webster, Medical Instrumentation Application and Design, 4th ed., John Wiley & Sons, Inc, 2010, pp. 109-110.
• [9] S. Butterworth, "On the Theory of Filter Amplifiers," Experimental Wireless & the wireless engineer, vol. 7, pp. 536-541, October 1930.
• [10] F. Holmqvist, P. G. Platonov, R. Havmöller and J. Carlson, "Signal-averaged P wave analysis for delineation of interatrial conduction – Further validation of the method," BMC Cardiovascular Disorders, Lund, Sweden, 2007.
• [11] P. S. Addison, "Wavelet transforms and the ECG: a review," PHYSIOLOGICAL MEASUREMENT, vol. 26, pp. 155-199, 2005.
• [12] B. Xhaja, E. Kalluci and L. Nikolla, "WAVELET TRANSFORM APPLIED IN ECG SIGNAL PROCESSING," European Scientific Journal, vol. 11, no. 12, April 2015.
• [13] "LabVIEW for ECG Signal Processing," National Instruments Tutorials, 2012.
• [14] M. Alfaouri and K. Daqrouq, "ECG Signal Denoising By Wavelet Transform Thresholding," American Journal of Applied Sciences, vol. 5, no. 3, pp. 76-281, 2008.
• [15] F. Hajiaghababa, S. Kermani and H. R. Marateb, "An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing," Journal of Medical Signals and Sensors, vol. 4, no. 4, pp. 247-255, 2014.
• [16] M. Z. Rad, S. R. Ghuchani, K. Bahaadinbeigy and M. M. Khalilzadeh, "Real Time Recognition of Heart Attack in a Smart Phone," ACTA INFORM MED, vol. 23, pp. 151-154, 2015.
• [17] V. Sharmila and A. K. Reddy, "Identification of Premature Ventricular Cycles of Electrocardiogram Using Discrete Cosine Transform-Teager Energy Operator Model," Journal of Medical Engineering, vol. Article ID 438569, 2015.
• [18] B. Cingozbay, E. Demiralp, E. Kardesoglu, B. Cebeci and M. Dincturk, "Effect of Smoking on Heart Rate Variability," Kosuyolu Heart Journal, vol. 5, no. 2, 2001.
• [19] G. Papathanasiou, D. Georgakopoulos, E. Papageorgiou, E. Zerva, L. Michalis, V. Kalfakakou and A. Evangelou, "Effects of Smoking on Heart Rate at Rest and During Exercise, and on Heart Rate Recovery, in Young Adults," Hellenic Journal of Cardiology, no. 54, pp. 168-177, 2013.
• [20] K. IS, R. MA and I. T, "Effect of Smoking on Heart Rate," Dinajpur Med Col J, vol. 8, no. 2, pp. 222-225, 2015.