Research Article
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Year 2021, , 362 - 371, 15.12.2021
https://doi.org/10.35860/iarej.917832

Abstract

Supporting Institution

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

Project Number

119E659

References

  • 1. Do Vale Madeiro, J.P., Cortez, P.C., Salinet, J.L., Pedrosa, R.C., da Silva Monteiro Filho, J.M., and Brayner, A.R.A., Classical and Modern Features for Interpretation of ECG Signal., Developments and Applications for ECG Signal Processing: Modeling, Segmentation, and Pattern Recognition, Elsevier, 2019. p. 1–28.
  • 2. Yang, S., Lam, B., and Ng, C.M.N., Calibration of Electrocardiograph (ECG) Simulators. NCSLI Measure, 2018. 12(1): p. 46–53.
  • 3. Koyuncu, İ., Özcerit, A.T., Pehlivan, İ., and Avaroğlu, E., Design and implementation of chaos based true random number generator on FPGA. In 2014 22nd IEEE Signal Processing and Communications Applications Conference, 2014. p. 236–239.
  • 4. Meyer-Base, U., Introduction., Digital Signal Processing with Field Programmable Gate Arrays, Berlin, Heidelberg, 2014. p. 1–52.
  • 5. Life in the fast lane. ECG Library Basics. [cited 2021 11 February]; Available from: https://litfl.com/ecg-library/.
  • 6. PhysioNet. The research resource for complex physiologic signals. Physio Bank ATM, MIT, and BIH Arrhythmia Database. [cited 2021 11 February]; Available from: https://archive.physionet.org/.
  • 7. Kumar, S., Singh, G., and Kaur, M., FPGA Implementation of Electrocardiography (ECG) Signal Processing 1. An International Journal of Engineering Sciences, 2016. p. 2229–6913.
  • 8. Desai, V., Electrocardiogram (ECG/EKG) using FPGA, San Jose State University, Computer Science, Master's Thesis, USA, 2012. p. 11-15.
  • 9. Madiraju, N.S., Kurella, N., and Valapudasu, R., FPGA Implementation of ECG Feature Extraction Using Time Domain Analysis. Electrical Engineering and Systems Science, Signal Processing (eess.SP); Hardware Architecture (cs.AR), 2018. arXiv:1802.03310.
  • 10. Agrawal, A., and Gawali, D.H., FPGA-Based Peak Detection of ECG Signal Using Histogram Approach., International Conference on Recent Innovations in Signal Processing and Embedded Systems, RISE 2017, Institute of Electrical and Electronics Engineers Inc., 2017. p. 463–468.
  • 11. Alhelal, D., and Faezipour, M., Denoising and Beat Detection of ECG Signal by Using FPGA. International Journal of High Speed Electronics and Systems, 2017. 26(3): p. 1740016.
  • 12. Su, W., Liang, Y., Li, M., and Li, Y., The Research and FPGA Implementation of ECG Signal Preprocessing., International Conference on Biomedical and Health Informatics, IFMBE Proceedings, Springer Verlag, Singapore, 2018. p. 167–168.
  • 13. Popa, R., ECG Signal Filtering in FPGA, 2019 6th International Symposium on Electrical and Electronics Engineering, ISEEE 2019, Galati, Romania, 2019. p. 1-6.
  • 14. Egila, M.G., El-Moursy, M.A., El-Hennawy, A. E., El-Simary, H.A., and Zaki, A., FPGA-Based Electrocardiography (ECG) Signal Analysis System Using Least-Square Linear Phase Finite Impulse Response (FIR) Filter. Journal of Electrical Systems and Information Technology, 2016. 3(3): p. 513–526.
  • 15. Shirzadfar, H., and Khanahmadi, M., Design and Development of ECG Simulator and Microcontroller Based Displayer. Journal of Biosensors & Bioelectronics, 2018. 9(3): p. 1–9.
  • 16. Cho, S., Lee, Y., and Chang, I., Designing a Novel ECG Simulator: Multi-Modality Electrocardiography into a Three-Dimensional Wire Cube Network. IEEE Technology and Society Magazine, 2016. 35(1): p. 75–84.
  • 17. Paul, A.D., Urzoshi, K.R., Datta, R.S., Arsalan, A., Azad, A.M., Design and Development of Microcontroller Based ECG Simulator, In: Osman, N.A.A., Abas, W.A.B.W., Wahab, A.K.A., Ting, HN. (eds) 5th Kuala Lumpur International Conference on Biomedical Engineering, IFMBE Proceedings, Berlin, Heidelberg, 2011. 35: p. 292-295.
  • 18. Jun-an, Z., The Design of ECG Signal Generator using PIC24F, Procedia Engineering, International Conference on Advances in Engineering, 2011. 24: p. 523-527.
  • 19. Chien, J.R.C., Design of a Programmable Electrocardi-ogram Generator Using a Microcontroller and the CPLD Technology, IECON Proceedings (Industrial Electronics Conference), IEEE Computer Society, 2007. p. 2152–2157.
  • 20. Caner, C., Engin, M., and Engin, E.Z., The Programmable ECG Simulator. Journal of Medical Systems, 2008. 32(4): p. 355–359.
  • 21. Karatas, F., Koyuncu, I., Alçın, M., and Tuna, M., Design of FPGA-based ECG Signal Using VHDL, 1st International Hazar Scientific Research Congress, IKSAD Publishing, Baku, Azerbaijan, 2020. p. 114–127.
  • 22. John, A.D., and Fleisher, L.A., Electrocardiography: The ECG. Anesthesiology Clinics of North America, 2006. 24(4): p. 697–715.
  • 23. Alemzadeh-Ansari, M.J., Editor(s): Maleki, M., Alizadehasl, A., Haghjoo, M., Chapter 3 Electrocardiography, Practical Cardiology, 2018. p. 17-60.
  • 24. Wagner, G., Chapter 6-Basic Electrocardiography, Editor(s): Saksena, S., Camm, A.J., Boyden, P.A., Dorian, P., Goldschlager, N., Electrophysiological Disorders of the Heart, Churchill Livingstone, 2005. p. 95-128.
  • 25. SkillStat. Free ECG Simulator. [cited 2021 12 February]; Available from: https://www.skillstat.com/tools/ecg-simulator/.
  • 26. Tlelo-Cuautle, E., Rangel-Magdaleno, J., de la Fraga, L. G., Tlelo-Cuautle, E., Rangel-Magdaleno, J. de J., and De la Fraga, L. G., Introduction to Field-Programmable Gate Arrays., Engineering Applications of FPGAs, Springer International Publishing, 2016. p. 1–32.
  • 27. Alcin, M., Tuna, M., Erdogmuş, P., and Koyuncu, I., FPGA-based Dual Core TRNG Design Using Ring and Runge-Kutta-Butcher based on Chaotic Oscillator. Chaos Theory and Applications, 2021. 3(1): p. 20–28.
  • 28. Moysis, L., Tutueva, A., Volos, C., and Butusov, D., A Chaos Based Pseudo-Random Bit Generator Using Multiple Digits Comparison. Chaos Theory and Applications, 2020. 2(2): p. 58–68.
  • 29. Alçın, M., Pehlivan, İ., and Koyuncu, İ., Hardware Design and Implementation of a Novel ANN-Based Chaotic Generator in FPGA. Optik - International Journal for Light and Electron Optics, 2016. 127(13): p. 5500–5505.
  • 30. Karataş, F., Koyuncu, İ., Tuna, M., and Alçın, M., Bulanık Mantık Üyelik Fonksiyonlarının Fpga Üzerinde Gerçeklenmesi. Bilgisayar Bilimleri ve Teknolojileri Dergisi, 2020. 1(1): p. 1-9.
  • 31. Akgul, A., Calgan, H., Koyuncu, I., Pehlivan, I., and Istanbullu, A., Chaos-Based Engineering Applications with a 3D Chaotic System without Equilibrium Points. Nonlinear Dynamics, 2015. 84(2): p. 481–495.
  • 32. Akgül, A., Arslan, C., Arıcıoğlu, B., Design of an Interface for Random Number Generators based on Integer and Fractional Order Chaotic Systems. Chaos Theory and Applications, 2019. 1(1): p. 1–18.
  • 33. Pan, J., Luan, F., Gao, Y., and Wei, Y., FPGA-Based Implementation of Stochastic Configuration Network for Robotic Grasping Recognition. IEEE Access, 2020. 8: p. 139966–139973.
  • 34. Fu, H., Osborne, W., Clapp, R. G., Mencer, O., and Luk, W., Accelerating Seismic Computations Using Customized Number Representations on FPGAs. Eurasip Journal on Embedded Systems, 2009. 2009: 382983.
  • 35. Koyuncu, I., Cetin, O., Katircioglu, F., and Tuna, M., Edge Dedection Application with FPGA Based Sobel Operator, 23nd Signal Processing and Communications Applications Conference (SIU), IEEE, Malatya, Turkey, 2015. p. 1829–1832.
  • 36. Taşdemir, M.F, Koyuncu, I., Coşgun, E., and Katırcıoglu, F., Real-Time Fast Corner Detection Algorithm Based Image Processing Application on FPGA, International Asian Congress on Contemporary Sciences-III, IKSAD Publishing, Konya, Türkiye, 2020. p. 1–6.
  • 37. Arshad, Shaukat, S., Ali, A., Eleyan, A., Shah, S., and Ahmad, J., Chaos Theory and its Application: An Essential Framework for Image Encryption. Chaos Theory and Applications, 2020. 2(1): p. 17–22.
  • 38. Chowdhury, S.R., Chakrabarti, D., and Saha, H., FPGA Realization of a Smart Processing System for Clinical Diagnostic Applications Using Pipelined Datapath Architectures. Microprocessors and Microsystems, 2008. 32(2): p. 107–120.
  • 39. Tuncer, T., Avaroglu, E., Türk, M., and Ozer, A.B., Implementation of non-periodic sampling true random number generator on FPGA. Informacije Midem, 2015. 44(4): p. 296–302.
  • 40. Alinx Electronics Technology, ZYNQ FPGA Development Board AX7020 User Manual. [cited 2021 9 February]; Available from: http://www.alinx.com/en/.

Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications

Year 2021, , 362 - 371, 15.12.2021
https://doi.org/10.35860/iarej.917832

Abstract

Biomedical applications are one of the important research areas of recent years. One of these fields of study is biomedical signals. In this study, the Normal Sinus Rhythm and three arrhythmic ECG signals (Ventricular Tachycardia, Ventricular Paced and Atrial Flutter), one of the vital sign signals, were designed and implemented to work on FPGA chips using the Xilinx-Vivado program with VHDL. Matlab-based ECG signals were taken as a reference and compared with the results obtained from the FPGA-based ECG signals design. Then, the structure used in the design and the test results obtained from the study have been presented. The designed ECG signals were synthesized for the Zynq-7000 XC7Z020 FPGA and observed from the oscilloscope using the 14-channel AN9767 DA module. FPGA chip resource consumption values obtained after the Place-Route process are presented. According to the results, the maximum operating frequency of Normal Sinus Rhythm and Ventricular tachycardia signals on the FPGA was 657.614 MHz and the maximum operating frequency of the Ventricular Paced and Atrial Flutter signals on the FPGA was 651.827 MHz. The maximum MSE value obtained from FPGA-based ECG signal design is 1.2319E-02. In this study, it has been shown that the FPGA-based ECG signal generation system, which is implemented as hardware, can be designed using FPGA chips and can be safely used in biomedical calibration applications. Other arrhythmic ECG signals can be designed and implemented using similar methods in future studies.

Project Number

119E659

References

  • 1. Do Vale Madeiro, J.P., Cortez, P.C., Salinet, J.L., Pedrosa, R.C., da Silva Monteiro Filho, J.M., and Brayner, A.R.A., Classical and Modern Features for Interpretation of ECG Signal., Developments and Applications for ECG Signal Processing: Modeling, Segmentation, and Pattern Recognition, Elsevier, 2019. p. 1–28.
  • 2. Yang, S., Lam, B., and Ng, C.M.N., Calibration of Electrocardiograph (ECG) Simulators. NCSLI Measure, 2018. 12(1): p. 46–53.
  • 3. Koyuncu, İ., Özcerit, A.T., Pehlivan, İ., and Avaroğlu, E., Design and implementation of chaos based true random number generator on FPGA. In 2014 22nd IEEE Signal Processing and Communications Applications Conference, 2014. p. 236–239.
  • 4. Meyer-Base, U., Introduction., Digital Signal Processing with Field Programmable Gate Arrays, Berlin, Heidelberg, 2014. p. 1–52.
  • 5. Life in the fast lane. ECG Library Basics. [cited 2021 11 February]; Available from: https://litfl.com/ecg-library/.
  • 6. PhysioNet. The research resource for complex physiologic signals. Physio Bank ATM, MIT, and BIH Arrhythmia Database. [cited 2021 11 February]; Available from: https://archive.physionet.org/.
  • 7. Kumar, S., Singh, G., and Kaur, M., FPGA Implementation of Electrocardiography (ECG) Signal Processing 1. An International Journal of Engineering Sciences, 2016. p. 2229–6913.
  • 8. Desai, V., Electrocardiogram (ECG/EKG) using FPGA, San Jose State University, Computer Science, Master's Thesis, USA, 2012. p. 11-15.
  • 9. Madiraju, N.S., Kurella, N., and Valapudasu, R., FPGA Implementation of ECG Feature Extraction Using Time Domain Analysis. Electrical Engineering and Systems Science, Signal Processing (eess.SP); Hardware Architecture (cs.AR), 2018. arXiv:1802.03310.
  • 10. Agrawal, A., and Gawali, D.H., FPGA-Based Peak Detection of ECG Signal Using Histogram Approach., International Conference on Recent Innovations in Signal Processing and Embedded Systems, RISE 2017, Institute of Electrical and Electronics Engineers Inc., 2017. p. 463–468.
  • 11. Alhelal, D., and Faezipour, M., Denoising and Beat Detection of ECG Signal by Using FPGA. International Journal of High Speed Electronics and Systems, 2017. 26(3): p. 1740016.
  • 12. Su, W., Liang, Y., Li, M., and Li, Y., The Research and FPGA Implementation of ECG Signal Preprocessing., International Conference on Biomedical and Health Informatics, IFMBE Proceedings, Springer Verlag, Singapore, 2018. p. 167–168.
  • 13. Popa, R., ECG Signal Filtering in FPGA, 2019 6th International Symposium on Electrical and Electronics Engineering, ISEEE 2019, Galati, Romania, 2019. p. 1-6.
  • 14. Egila, M.G., El-Moursy, M.A., El-Hennawy, A. E., El-Simary, H.A., and Zaki, A., FPGA-Based Electrocardiography (ECG) Signal Analysis System Using Least-Square Linear Phase Finite Impulse Response (FIR) Filter. Journal of Electrical Systems and Information Technology, 2016. 3(3): p. 513–526.
  • 15. Shirzadfar, H., and Khanahmadi, M., Design and Development of ECG Simulator and Microcontroller Based Displayer. Journal of Biosensors & Bioelectronics, 2018. 9(3): p. 1–9.
  • 16. Cho, S., Lee, Y., and Chang, I., Designing a Novel ECG Simulator: Multi-Modality Electrocardiography into a Three-Dimensional Wire Cube Network. IEEE Technology and Society Magazine, 2016. 35(1): p. 75–84.
  • 17. Paul, A.D., Urzoshi, K.R., Datta, R.S., Arsalan, A., Azad, A.M., Design and Development of Microcontroller Based ECG Simulator, In: Osman, N.A.A., Abas, W.A.B.W., Wahab, A.K.A., Ting, HN. (eds) 5th Kuala Lumpur International Conference on Biomedical Engineering, IFMBE Proceedings, Berlin, Heidelberg, 2011. 35: p. 292-295.
  • 18. Jun-an, Z., The Design of ECG Signal Generator using PIC24F, Procedia Engineering, International Conference on Advances in Engineering, 2011. 24: p. 523-527.
  • 19. Chien, J.R.C., Design of a Programmable Electrocardi-ogram Generator Using a Microcontroller and the CPLD Technology, IECON Proceedings (Industrial Electronics Conference), IEEE Computer Society, 2007. p. 2152–2157.
  • 20. Caner, C., Engin, M., and Engin, E.Z., The Programmable ECG Simulator. Journal of Medical Systems, 2008. 32(4): p. 355–359.
  • 21. Karatas, F., Koyuncu, I., Alçın, M., and Tuna, M., Design of FPGA-based ECG Signal Using VHDL, 1st International Hazar Scientific Research Congress, IKSAD Publishing, Baku, Azerbaijan, 2020. p. 114–127.
  • 22. John, A.D., and Fleisher, L.A., Electrocardiography: The ECG. Anesthesiology Clinics of North America, 2006. 24(4): p. 697–715.
  • 23. Alemzadeh-Ansari, M.J., Editor(s): Maleki, M., Alizadehasl, A., Haghjoo, M., Chapter 3 Electrocardiography, Practical Cardiology, 2018. p. 17-60.
  • 24. Wagner, G., Chapter 6-Basic Electrocardiography, Editor(s): Saksena, S., Camm, A.J., Boyden, P.A., Dorian, P., Goldschlager, N., Electrophysiological Disorders of the Heart, Churchill Livingstone, 2005. p. 95-128.
  • 25. SkillStat. Free ECG Simulator. [cited 2021 12 February]; Available from: https://www.skillstat.com/tools/ecg-simulator/.
  • 26. Tlelo-Cuautle, E., Rangel-Magdaleno, J., de la Fraga, L. G., Tlelo-Cuautle, E., Rangel-Magdaleno, J. de J., and De la Fraga, L. G., Introduction to Field-Programmable Gate Arrays., Engineering Applications of FPGAs, Springer International Publishing, 2016. p. 1–32.
  • 27. Alcin, M., Tuna, M., Erdogmuş, P., and Koyuncu, I., FPGA-based Dual Core TRNG Design Using Ring and Runge-Kutta-Butcher based on Chaotic Oscillator. Chaos Theory and Applications, 2021. 3(1): p. 20–28.
  • 28. Moysis, L., Tutueva, A., Volos, C., and Butusov, D., A Chaos Based Pseudo-Random Bit Generator Using Multiple Digits Comparison. Chaos Theory and Applications, 2020. 2(2): p. 58–68.
  • 29. Alçın, M., Pehlivan, İ., and Koyuncu, İ., Hardware Design and Implementation of a Novel ANN-Based Chaotic Generator in FPGA. Optik - International Journal for Light and Electron Optics, 2016. 127(13): p. 5500–5505.
  • 30. Karataş, F., Koyuncu, İ., Tuna, M., and Alçın, M., Bulanık Mantık Üyelik Fonksiyonlarının Fpga Üzerinde Gerçeklenmesi. Bilgisayar Bilimleri ve Teknolojileri Dergisi, 2020. 1(1): p. 1-9.
  • 31. Akgul, A., Calgan, H., Koyuncu, I., Pehlivan, I., and Istanbullu, A., Chaos-Based Engineering Applications with a 3D Chaotic System without Equilibrium Points. Nonlinear Dynamics, 2015. 84(2): p. 481–495.
  • 32. Akgül, A., Arslan, C., Arıcıoğlu, B., Design of an Interface for Random Number Generators based on Integer and Fractional Order Chaotic Systems. Chaos Theory and Applications, 2019. 1(1): p. 1–18.
  • 33. Pan, J., Luan, F., Gao, Y., and Wei, Y., FPGA-Based Implementation of Stochastic Configuration Network for Robotic Grasping Recognition. IEEE Access, 2020. 8: p. 139966–139973.
  • 34. Fu, H., Osborne, W., Clapp, R. G., Mencer, O., and Luk, W., Accelerating Seismic Computations Using Customized Number Representations on FPGAs. Eurasip Journal on Embedded Systems, 2009. 2009: 382983.
  • 35. Koyuncu, I., Cetin, O., Katircioglu, F., and Tuna, M., Edge Dedection Application with FPGA Based Sobel Operator, 23nd Signal Processing and Communications Applications Conference (SIU), IEEE, Malatya, Turkey, 2015. p. 1829–1832.
  • 36. Taşdemir, M.F, Koyuncu, I., Coşgun, E., and Katırcıoglu, F., Real-Time Fast Corner Detection Algorithm Based Image Processing Application on FPGA, International Asian Congress on Contemporary Sciences-III, IKSAD Publishing, Konya, Türkiye, 2020. p. 1–6.
  • 37. Arshad, Shaukat, S., Ali, A., Eleyan, A., Shah, S., and Ahmad, J., Chaos Theory and its Application: An Essential Framework for Image Encryption. Chaos Theory and Applications, 2020. 2(1): p. 17–22.
  • 38. Chowdhury, S.R., Chakrabarti, D., and Saha, H., FPGA Realization of a Smart Processing System for Clinical Diagnostic Applications Using Pipelined Datapath Architectures. Microprocessors and Microsystems, 2008. 32(2): p. 107–120.
  • 39. Tuncer, T., Avaroglu, E., Türk, M., and Ozer, A.B., Implementation of non-periodic sampling true random number generator on FPGA. Informacije Midem, 2015. 44(4): p. 296–302.
  • 40. Alinx Electronics Technology, ZYNQ FPGA Development Board AX7020 User Manual. [cited 2021 9 February]; Available from: http://www.alinx.com/en/.
There are 40 citations in total.

Details

Primary Language English
Subjects Software Engineering, Electrical Engineering
Journal Section Research Articles
Authors

Fatih Karataş 0000-0003-1877-5552

İsmail Koyuncu 0000-0003-4725-4879

Murat Alçın 0000-0002-2874-7048

Murat Tuna 0000-0003-3511-1336

Project Number 119E659
Publication Date December 15, 2021
Submission Date April 16, 2021
Acceptance Date July 8, 2021
Published in Issue Year 2021

Cite

APA Karataş, F., Koyuncu, İ., Alçın, M., Tuna, M. (2021). Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications. International Advanced Researches and Engineering Journal, 5(3), 362-371. https://doi.org/10.35860/iarej.917832
AMA Karataş F, Koyuncu İ, Alçın M, Tuna M. Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications. Int. Adv. Res. Eng. J. December 2021;5(3):362-371. doi:10.35860/iarej.917832
Chicago Karataş, Fatih, İsmail Koyuncu, Murat Alçın, and Murat Tuna. “Design and Implementation of FPGA-Based Arrhythmic ECG Signals Using VHDL for Biomedical Calibration Applications”. International Advanced Researches and Engineering Journal 5, no. 3 (December 2021): 362-71. https://doi.org/10.35860/iarej.917832.
EndNote Karataş F, Koyuncu İ, Alçın M, Tuna M (December 1, 2021) Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications. International Advanced Researches and Engineering Journal 5 3 362–371.
IEEE F. Karataş, İ. Koyuncu, M. Alçın, and M. Tuna, “Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications”, Int. Adv. Res. Eng. J., vol. 5, no. 3, pp. 362–371, 2021, doi: 10.35860/iarej.917832.
ISNAD Karataş, Fatih et al. “Design and Implementation of FPGA-Based Arrhythmic ECG Signals Using VHDL for Biomedical Calibration Applications”. International Advanced Researches and Engineering Journal 5/3 (December 2021), 362-371. https://doi.org/10.35860/iarej.917832.
JAMA Karataş F, Koyuncu İ, Alçın M, Tuna M. Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications. Int. Adv. Res. Eng. J. 2021;5:362–371.
MLA Karataş, Fatih et al. “Design and Implementation of FPGA-Based Arrhythmic ECG Signals Using VHDL for Biomedical Calibration Applications”. International Advanced Researches and Engineering Journal, vol. 5, no. 3, 2021, pp. 362-71, doi:10.35860/iarej.917832.
Vancouver Karataş F, Koyuncu İ, Alçın M, Tuna M. Design and implementation of FPGA-based arrhythmic ECG signals using VHDL for biomedical calibration applications. Int. Adv. Res. Eng. J. 2021;5(3):362-71.



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