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EEG Sinyallerinin İşlenmesi için İkinci Nesil Akım Kontrollü Akım Taşıyıcı Tabanlı Alçak Geçiren Filtre Tasarımı

Year 2023, Volume: 18 Issue: 2, 405 - 413, 01.09.2023
https://doi.org/10.55525/tjst.1243178

Abstract

EEG sinyalleri, beyin aktvitesinin analiz edilmesini sağlayan gürültülü sinyallerdir. Son yıllarda, bu sinyallerin analizinde işlemsel yükselteçlerin yerine geniş bant aralığı, yüksek doğrusallık, düşük güç tüketimi gibi birçok avantaj sahip olan akım taşıyıcı tabanlı devrelerin kullanıldığı görülmüştür. Bu çalışmada EEG sinyallerinin analizi için 100 Hz kesim frekansına sahip bir ikinci nesil akım kontrollü akım taşıyıcı (CCCII+) alçak geçiren filtre devresi sunulmuştur. Devrenin benzetimi Orcad pspice programı ile gerçekleştirilmiştir. Ayrıca bu alçak geçiren filtre devresinin uygulama devresi yapılmış ve bazı frekans değerleri için osiloskop görüntüleri elde edilmiştir. Uygulama devresinde akım taşıyıcı olarak AD844 IC kullanılmıştır. CCCII+ alçak geçiren filtre devresine, Bonn Üniversitesinden alınan epilepsi hastası ve normal kişilere ait veriler uygulanmış ve bu sinyallerin frekans bantları incelenmiştir. Bu CCCII+ alçak geçiren filtre devresinin EEG ölçümlerinde kullanılması durumunda epilepsi gibi nörolojik hastalıkların tanısında iyi sonuçlar vereceği öngörülmüştür.

References

  • Yazgan E, Korürek M. Tıp Elektroniği. Ofset Baskı Atölyesi 1996; İstanbul.
  • Stern JM, Engel J. Atlas of EEG Patterns. Lippincott Williams & Wilkins 2005; California, USA.
  • Sanei S, Chambers JA. EEG signal processing. John Wiley & Sons 2007; London.
  • Aydemir Ö, Kayıkçıoğlu T. EEG Tabanlı Beyin Bilgisayar Arayüzleri. Akademik Bilişim’09 - XI. Akademik Bilişim Konferansı Bildirileri 2009; Harran Üniversitesi, Şanlıurfa; 7-13.
  • Dimalanta VSM, Hubilla BCR, Marquez JCJS, Quiambao VPT, Tungala KL, Prado SV. Correlation of Emotion to Film Rating Classification Using EEG Signal Analysis. 5th. International Electrical Engineering Congress 2017; Thailand; 1-4.
  • Abdallah A, Diab M, Mahmoud S. A Micropower EEG Detection System Applicable for Paralyzed Hand Artificial Control. 40th International Conference on Telecommunications and Signal Processing 2017; Spain; 411-414.
  • Lerga J, Saulig N, Lerga R, Stajduhar I. TFD Thresholding in Estimating The Number of EEG Components and The Dominant IF Using The Short-Term Renyi Entropy. International Symposium on Image and Signal Processing and Analysis 2017; Slovenia; 80-85.
  • Aydemir Ö. Combining Sub-band Power Features Extracted from Different Time Segments of EEG Trials. 40th International Conference on Telecommunications and Signal Processing 2017; Spain; 383-386.
  • Kitiş Ş, Apaydın H, Güntürkün R. Designed Filter with CCII+ and Analysis of EEG for Epilepsy and Alzheimer. Acta Phys. Pol. A 2017; 132(3): 423-426.
  • Karami Horestani F, Karami Horastani Z, Björsell N. Band-Pass Instrumentation Amplifier Based on a Differential Voltage Current Conveyor for Biomedical Signal Recording Applications. Electronics 2022; 11(7): 1087.
  • Karami Horestani F, Eshghi M, Yazdchi M. An ultra-low power amplifier for wearable and implantable electronic devices. Microelectronic Engineering 2019; 216: 111054.
  • Stornelli V, Ferri G. A Single Current Conveyor-based Low Voltage Low PowerBootstrap Circuit for ElectroCardioGraphy and ElectroEncephaloGraphy Acquisition Systems. Analog Integr. Circuits Signal Process., 2014; 79(1): 171-175.
  • Kumngern M, Khateb F, Kulej T.Extremely low-voltage low-power differential difference current conveyor using multiple-input bulk-driven technique. AEU Int. J. Electron. Commun 2020; 123: 1-11.
  • Psychalinos C, Minaei S, Safari L. Ultra low-power electronically tunable current-mode instrumentation amplifier for biomedical applications. AEU Int. J. Electron. Commun 2020; 117: 153-120.
  • Andrzejak RG, Lehnertz K, Rieke C, Mormann F, David P, Elger CE. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Phys. Rev. E, 2001; 64: 061907.
  • Fabre A, Saaid O, Wiest F, Boucheron C. Current controlled bandpass filter based on translinear conveyors. Electron. Lett. 1995; 31(20): 1727-1728.
  • Fabre A, Alami M. Universal current-mode biquad implemented from two second-generation current conveyors. IEEE Trans. Circuits Syst. I: Fund.Theo. and Appl. 1995; 42(7): 383−385.
  • Analog Devices AD844. 60 MHz 2000 V/μs Monolithic Op Amp. Rev. 2017.
  • Paul SK, Choubey CK, Tiwari G. Low power analog comb filter for biomedical applications. Analog Integr. Circuits Signal Process 2018; 97: 371-386.
  • Fabre A, Saaid O, Wiest F, Boucheron C. High-frequency application based on a new current controlled conveyor. IEEE Trans. Circuits Syst. I: Fund.Theo. and Appl. 1996; 43(2): 82-91.

Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals

Year 2023, Volume: 18 Issue: 2, 405 - 413, 01.09.2023
https://doi.org/10.55525/tjst.1243178

Abstract

EEG signals are noisy signals that allow brain activity to be analyzed. In recent years, it has been seen that current conveyor-based circuits, which have many advantages such as wide bandwidth, high linearity, low power consumption, have been used instead of operational amplifiers in the analysis of these signals. In this study, a second-generation current controlled current conveyor (CCCII+) low pass filter circuit with a cut-off frequency of 100 Hz has been presented for the analysis of EEG signals. The simulation of the circuit was carried out with the Orcad pspice program. In addition, the application circuit of this low-pass filter circuit has been made and oscilloscope images have been obtained for some frequency values. AD844 IC is used as current conveyor in the application circuit. The data of epilepsy patients and normal people taken from the University of Bonn were applied to the CCCII+ low pass filter circuit and the frequency bands of these signals were examined. It has been predicted that if this CCCII+ low pass filter circuit is used in EEG measurements, it will give good results in the diagnosis of neurological diseases such as epilepsy.

References

  • Yazgan E, Korürek M. Tıp Elektroniği. Ofset Baskı Atölyesi 1996; İstanbul.
  • Stern JM, Engel J. Atlas of EEG Patterns. Lippincott Williams & Wilkins 2005; California, USA.
  • Sanei S, Chambers JA. EEG signal processing. John Wiley & Sons 2007; London.
  • Aydemir Ö, Kayıkçıoğlu T. EEG Tabanlı Beyin Bilgisayar Arayüzleri. Akademik Bilişim’09 - XI. Akademik Bilişim Konferansı Bildirileri 2009; Harran Üniversitesi, Şanlıurfa; 7-13.
  • Dimalanta VSM, Hubilla BCR, Marquez JCJS, Quiambao VPT, Tungala KL, Prado SV. Correlation of Emotion to Film Rating Classification Using EEG Signal Analysis. 5th. International Electrical Engineering Congress 2017; Thailand; 1-4.
  • Abdallah A, Diab M, Mahmoud S. A Micropower EEG Detection System Applicable for Paralyzed Hand Artificial Control. 40th International Conference on Telecommunications and Signal Processing 2017; Spain; 411-414.
  • Lerga J, Saulig N, Lerga R, Stajduhar I. TFD Thresholding in Estimating The Number of EEG Components and The Dominant IF Using The Short-Term Renyi Entropy. International Symposium on Image and Signal Processing and Analysis 2017; Slovenia; 80-85.
  • Aydemir Ö. Combining Sub-band Power Features Extracted from Different Time Segments of EEG Trials. 40th International Conference on Telecommunications and Signal Processing 2017; Spain; 383-386.
  • Kitiş Ş, Apaydın H, Güntürkün R. Designed Filter with CCII+ and Analysis of EEG for Epilepsy and Alzheimer. Acta Phys. Pol. A 2017; 132(3): 423-426.
  • Karami Horestani F, Karami Horastani Z, Björsell N. Band-Pass Instrumentation Amplifier Based on a Differential Voltage Current Conveyor for Biomedical Signal Recording Applications. Electronics 2022; 11(7): 1087.
  • Karami Horestani F, Eshghi M, Yazdchi M. An ultra-low power amplifier for wearable and implantable electronic devices. Microelectronic Engineering 2019; 216: 111054.
  • Stornelli V, Ferri G. A Single Current Conveyor-based Low Voltage Low PowerBootstrap Circuit for ElectroCardioGraphy and ElectroEncephaloGraphy Acquisition Systems. Analog Integr. Circuits Signal Process., 2014; 79(1): 171-175.
  • Kumngern M, Khateb F, Kulej T.Extremely low-voltage low-power differential difference current conveyor using multiple-input bulk-driven technique. AEU Int. J. Electron. Commun 2020; 123: 1-11.
  • Psychalinos C, Minaei S, Safari L. Ultra low-power electronically tunable current-mode instrumentation amplifier for biomedical applications. AEU Int. J. Electron. Commun 2020; 117: 153-120.
  • Andrzejak RG, Lehnertz K, Rieke C, Mormann F, David P, Elger CE. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Phys. Rev. E, 2001; 64: 061907.
  • Fabre A, Saaid O, Wiest F, Boucheron C. Current controlled bandpass filter based on translinear conveyors. Electron. Lett. 1995; 31(20): 1727-1728.
  • Fabre A, Alami M. Universal current-mode biquad implemented from two second-generation current conveyors. IEEE Trans. Circuits Syst. I: Fund.Theo. and Appl. 1995; 42(7): 383−385.
  • Analog Devices AD844. 60 MHz 2000 V/μs Monolithic Op Amp. Rev. 2017.
  • Paul SK, Choubey CK, Tiwari G. Low power analog comb filter for biomedical applications. Analog Integr. Circuits Signal Process 2018; 97: 371-386.
  • Fabre A, Saaid O, Wiest F, Boucheron C. High-frequency application based on a new current controlled conveyor. IEEE Trans. Circuits Syst. I: Fund.Theo. and Appl. 1996; 43(2): 82-91.
There are 20 citations in total.

Details

Primary Language English
Subjects Electronics
Journal Section TJST
Authors

Kübra Tekin 0000-0002-6050-9760

Hasan Güler 0000-0002-9917-3619

Publication Date September 1, 2023
Submission Date January 27, 2023
Published in Issue Year 2023 Volume: 18 Issue: 2

Cite

APA Tekin, K., & Güler, H. (2023). Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals. Turkish Journal of Science and Technology, 18(2), 405-413. https://doi.org/10.55525/tjst.1243178
AMA Tekin K, Güler H. Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals. TJST. September 2023;18(2):405-413. doi:10.55525/tjst.1243178
Chicago Tekin, Kübra, and Hasan Güler. “Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals”. Turkish Journal of Science and Technology 18, no. 2 (September 2023): 405-13. https://doi.org/10.55525/tjst.1243178.
EndNote Tekin K, Güler H (September 1, 2023) Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals. Turkish Journal of Science and Technology 18 2 405–413.
IEEE K. Tekin and H. Güler, “Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals”, TJST, vol. 18, no. 2, pp. 405–413, 2023, doi: 10.55525/tjst.1243178.
ISNAD Tekin, Kübra - Güler, Hasan. “Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals”. Turkish Journal of Science and Technology 18/2 (September 2023), 405-413. https://doi.org/10.55525/tjst.1243178.
JAMA Tekin K, Güler H. Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals. TJST. 2023;18:405–413.
MLA Tekin, Kübra and Hasan Güler. “Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals”. Turkish Journal of Science and Technology, vol. 18, no. 2, 2023, pp. 405-13, doi:10.55525/tjst.1243178.
Vancouver Tekin K, Güler H. Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals. TJST. 2023;18(2):405-13.