Araştırma Makalesi
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Yıl 2017, Cilt: 2 Sayı: 2, 47 - 50, 01.12.2017

Öz

Kaynakça

  • [1] R. S. Fisher, W. Van Emde Boas, W. Blume et al., “Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE),”Epilepsia, vol.46, no.4,pp.470–472, 2005.
  • [2] S. Noachtar and J. Remi, “The role of EEG in epilepsy: a critical review,”Epilepsy and Behavior, vol.15, no.1, pp.22–33, 2009.
  • [3] W. Ku, R. H. Storer, and C. Georgakis, “Disturbance detection and isolation by dynamic principal component analysis,”Chemometrics and Intelligent Laboratory Systems, vol.30, no.1, pp.179–196,1995.
  • [4] V. P. Nigam and D. Graupe, “A neural-network-based detectionof epilepsy,”Neurological Research, vol.26, no.1, pp.55–60,2004.
  • [5] V. Srinivasan, C. Eswaran, and A. N. Sriraam, “Artificial neural network based epileptic detection using time-domain and frequency-domain features,”Journal of Medical Systems, vol.29, no. 6, pp. 647–660, 2005.
  • [6] Асанова Л.М., Чехонин В.П., Гавриленко А.Я. Иммуноферментный анализ нейроспецифических белков в сыворотке крови больных эпилепсией // Журн. неврологии и психиатрии им. С.С. Корсакова. 1995. Т. 95. № 3. С. 30—31.
  • [7] Гнездицкий В.В. Вызванные потенциалы головного мозга в клинической практике. М.: МЕДпресс-информ, 2003. 264 с. [8] Казаковцев Б.А. Психические расстройства при эпилепсии. М., 1999. 416 с.
  • [9] Коберская Н.Н, Зенков Л.Р, Захаров В.В., Преображенская И.С. Когнитивный потенциал Р300 при болезни Паркинсона и деменции с тельцами Леви // Неврол. журн. 2006. Прил. 1. С. 26—31.
  • [10] H. Kim and J. Rosen, “Epileptic seizure detection—an AR model based algorithm for implantable device,” in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC ’10) ,pp. 5541–5544, Buenos Aires, Argentina, September 2010.
  • [11] R. G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David, and C. E. Elger, “Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state,” Physical Review E, vol.64, no.6, Article ID 061907, 2001.
  • [12] https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project/eeg-database.
  • [13] N. E. Golyandina, V. V. Nekrutin, and A. A. Zhigljavsky, Analysis of Time Series Structure. SSA and Related Techniques, Chapman and Hall, Boca Raton, Fla, USA, 2001.
  • [14] J. R. G. Lansangan and E. B. Barrios, “Principal components analysis of nonstationary time series data”, Statistics and Computing, vol. 19, no.2, pp.173–187,2009.

ANALYSIS OF EPILEPTIC SIGNALS BASED ON DISCRETE HARTLEY TRANSFORM AND DISCRETE FOURIER TRANSFORM

Yıl 2017, Cilt: 2 Sayı: 2, 47 - 50, 01.12.2017

Öz

In this paper, the proposed approach to the problems
of assessing the rhythms of the brain develops an analysis is made of the
existing features of processing neurological signals. For the analysis of
epileptic discharges, which are the focus of work, it is proposed to use
orthogonal transformations. This was done on the basis of a reasoned model of
epileptic discharges as a class of broadband pulse signals. The analysis of the
main features of the discrete Fourier and Hartley transforms is presented as
the main methods of signal processing in the case of epileptic seizures is
carried out. The results of the analysis of the real, containing a fragment of
the epileptic discharge of the EEG record obtained on the basis of the proposed
approach are presented.

Kaynakça

  • [1] R. S. Fisher, W. Van Emde Boas, W. Blume et al., “Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE),”Epilepsia, vol.46, no.4,pp.470–472, 2005.
  • [2] S. Noachtar and J. Remi, “The role of EEG in epilepsy: a critical review,”Epilepsy and Behavior, vol.15, no.1, pp.22–33, 2009.
  • [3] W. Ku, R. H. Storer, and C. Georgakis, “Disturbance detection and isolation by dynamic principal component analysis,”Chemometrics and Intelligent Laboratory Systems, vol.30, no.1, pp.179–196,1995.
  • [4] V. P. Nigam and D. Graupe, “A neural-network-based detectionof epilepsy,”Neurological Research, vol.26, no.1, pp.55–60,2004.
  • [5] V. Srinivasan, C. Eswaran, and A. N. Sriraam, “Artificial neural network based epileptic detection using time-domain and frequency-domain features,”Journal of Medical Systems, vol.29, no. 6, pp. 647–660, 2005.
  • [6] Асанова Л.М., Чехонин В.П., Гавриленко А.Я. Иммуноферментный анализ нейроспецифических белков в сыворотке крови больных эпилепсией // Журн. неврологии и психиатрии им. С.С. Корсакова. 1995. Т. 95. № 3. С. 30—31.
  • [7] Гнездицкий В.В. Вызванные потенциалы головного мозга в клинической практике. М.: МЕДпресс-информ, 2003. 264 с. [8] Казаковцев Б.А. Психические расстройства при эпилепсии. М., 1999. 416 с.
  • [9] Коберская Н.Н, Зенков Л.Р, Захаров В.В., Преображенская И.С. Когнитивный потенциал Р300 при болезни Паркинсона и деменции с тельцами Леви // Неврол. журн. 2006. Прил. 1. С. 26—31.
  • [10] H. Kim and J. Rosen, “Epileptic seizure detection—an AR model based algorithm for implantable device,” in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC ’10) ,pp. 5541–5544, Buenos Aires, Argentina, September 2010.
  • [11] R. G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David, and C. E. Elger, “Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state,” Physical Review E, vol.64, no.6, Article ID 061907, 2001.
  • [12] https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project/eeg-database.
  • [13] N. E. Golyandina, V. V. Nekrutin, and A. A. Zhigljavsky, Analysis of Time Series Structure. SSA and Related Techniques, Chapman and Hall, Boca Raton, Fla, USA, 2001.
  • [14] J. R. G. Lansangan and E. B. Barrios, “Principal components analysis of nonstationary time series data”, Statistics and Computing, vol. 19, no.2, pp.173–187,2009.
Toplam 13 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Alla Horiushkina Bu kişi benim 0000-0002-4913-9674

Juliya Breslavets 0000-0003-4530-8028

Yayımlanma Tarihi 1 Aralık 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 2 Sayı: 2

Kaynak Göster

APA Horiushkina, A., & Breslavets, J. (2017). ANALYSIS OF EPILEPTIC SIGNALS BASED ON DISCRETE HARTLEY TRANSFORM AND DISCRETE FOURIER TRANSFORM. The Journal of Cognitive Systems, 2(2), 47-50.