Dergiler / Gazi University Journal of Science / 2026 / Volume: 35 Issue: 3

ARM MCU-Based Experimental EEG Signal Generator Using Internal DAC and PWM Outputs

Ertuğrul Karakulak(NAMIK KEMAL ÜNİVERSİTESİ, TEKNİK BİLİMLER MESLEK YÜKSEKOKULU)0000-0001-5937-2114
Sayfa
—
Yayın Tarihi
2022-09-01
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It has been shown that the experimental signals taken from the database can be generated by using cheap and easily accessible electronic devices.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Electrophysiological signal generators are widely used in biomedical engineering research, biomedical education and the testing of devices in hospitals.
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Temel Bulgular & Veri:In addition, the PWM and DAC outputs of the microcontroller are used and examined separately to generate the signal.
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Sonuç & Katkı:It has been shown that the experimental signals taken from the database can be generated by using cheap and easily accessible electronic devices.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Signal generator · Electroencephalograpram · Microcontroller

Abstract

Electrophysiological signal generators are widely used in biomedical engineering research, biomedical education and the testing of devices in hospitals. Such signal generators are also available commercially. The EEG (Electroencephalography) signal is an electrophysiological signal which is emitted from the brain. In this study, a signal generator that produces experimental EEG signals taken from databases is proposed. The proposed signal generator reads the experimental data from an SD card with SDIO serial protocol. In addition, the PWM and DAC outputs of the microcontroller are used and examined separately to generate the signal. It has been shown that the experimental signals taken from the database can be generated by using cheap and easily accessible electronic devices.

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Bu Makaleye Atıf Yap

Karakulak, E. (2022). ARM MCU-Based Experimental EEG Signal Generator Using Internal DAC and PWM Outputs. Gazi University Journal of Science, Volume: 35 Issue: 3. https://doi.org/10.35378/gujs.860994

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Kaynakça (14)

  1. Güçlü, B., “Low-cost computer-controlled current stimulator for the student laboratory,”, Advances in Physiology Education, 31(2): 223–231, (2007).
  2. Abiri, R., Borhani, S., Sellers, E. W., Jiang, Y., Zhao, X., "A comprehensive review of EEG-based brain–computer interface paradigms.", Journal of Neural Engineering 16(1), (2019).
  3. Balandong, R. P., Ahmad, R. F., Saad, M. N. M., Malik, A. S., "A review on EEG-based automatic sleepiness detection systems for driver.", IEEE Access, 6: 22908-22919, (2018).
  4. Shakir, M., Qidwai, U., Malik, A. S., Kamel, N., "Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation.", Journal of Medical Imaging and Health Informatics, 5(1): 43-49, (2015).
  5. Tejkl, L., Kudrna, P., Rafl, J., Svoboda, J., "Patient Simulators in Medical Education: New Enhancements.", 2019 E-Health and Bioengineering Conference (EHB), Lasi, Romania, 1-4, (2019).
  6. https://www.netechcorp.us/Products/details/330-EEG-Simulator_71. Access date: 01.01.2021
  7. Yener, S. C., Mutlu, R., "A microcontroller-based ECG signal generator design utilizing microcontroller PWM output and experimental ECG data.", 2018 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT), Istanbul, 1-4, (2018).
  8. Jun-an, Z., "The Design of ECG Signal Generator using PIC24F ", Procedia Engineering, 24: 523-527, (2011).
  9. Jun-an, Z., "The Design of ECG Signal Generator using PIC24F ", Procedia Engineering, 24: 523-527, (2011).
  10. Wei, Y. C., Wei, Y. Y., Wey, S. T., Jang, L. S., "Design of a programmable ecg generator using a dynamical model.", Applied Mechanics and Materials, 311:485-490, (2013).
  11. McSharry, P. E., Clifford, G. D., Tarassenko, L., Smith, L. A., “Dynamical model for generating synthetic electrocardiogram signals”, IEEE Transactions On Biomedical Engineering, 50: 289-294, (2003).
  12. https://sccn.ucsd.edu/~arno/fam2data/publicly_available_EEG_data.html. Access date: 01.01.2021
  13. Campisi, P., La Rocca, D., “Brain waves for automatic biometric-based user recognition”, IEEE Transactions on Information Forensics and Security, 9(5): 782–800, (2014).
  14. McSharry, P. E., Clifford, G. D., Tarassenko, L., Smith, L. A., “Dynamical model for generating synthetic electrocardiogram signals”, IEEE Transactions On Biomedical Engineering, 50: 289-294, (2003).