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Towards Personalized Neural Networks for Epileptic Seizure Prediction

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Artificial Neural Networks - ICANN 2008 (ICANN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5164))

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Abstract

Seizure prediction for untreatable epileptic patients, one of the major challenges of present neuroinformatics researchers, will allow a substantial improvement in their safety and quality of life. Neural networks, because of their plasticity and degrees of freedom, seem to be a good approach to consider the enormous variability of physiological systems. Several architectures and training algorithms are comparatively proposed in this work showing that it is possible to find an adequate network for one patient, but care must be taken to generalize to other patients. It is claimed that each patient will have his (her) own seizure prediction algorithms.

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References

  1. Browne, T., Holmes, G.: Handbook of epilepsy. Lippincott Williams & Wilkins (2000)

    Google Scholar 

  2. Mormann, F., Andrzejak, R.G., Elger, C.E., Lehnertz, K.: Seizure prediction: The long and winding road. Brain 130, 314–333 (2007)

    Article  Google Scholar 

  3. Schelter, B., Winterhalder, M., Feldwisch, G., Drentrup, H., Wohlmuth, J., Nawrath, J., Brandt, A., Schulze-Bonhage, A., Timmer, J.: Seizure prediction: The impact of long prediction horizons. Epilepsy research 73, 213–217 (2007)

    Article  Google Scholar 

  4. Guler, I., Ubeyli, E.D.: Application of adaptive neuro-fuzzy inference system for detection of electrocardiographic changes in patients with partial epilepsy using feature extraction. Expert Systems with Applications 27, 323–330 (2004)

    Article  Google Scholar 

  5. Subasi, A.: Application of adaptive neuro-fuzzy inference system for epileptic seizure detection using wavelet feature extraction. Computers in Biology and Medicine 37, 227–244 (2007)

    Article  Google Scholar 

  6. Litt, B., Esteller, R., Echauz, J., D’Alessandro, M., Shor, R., Henry, T., et al.: Epileptic seizures may begin hours in advance of clinical onset: a report of five patients. Neuron 30, 51–64 (2001)

    Article  Google Scholar 

  7. Esteller, R., Echauz, J., D’Alessandro, M., Worrell, G., et al.: Continuous energy variation during the seizure cycle: towards an on-line accumulated energy. Clinical Neurophysiology 116, 517–526 (2005)

    Article  Google Scholar 

  8. Gigola, S., Ortiz, F., D’Atellis, C., Silva, W., Kochen, S.: Prediction of epileptic seizures using accumulated energy in a multiresolution framework. Journal of Neuroscience Methods 138, 107–111 (2004)

    Article  Google Scholar 

  9. Chaovalitwongse, W., Iasemidis, L.D., Pardalos, P.M., Carney, P.R., Shiau, D.S., Sackellares, J.C.: Performance of a seizure warning algorithm based on the dynamics of intracranial EEG. Epilepsy 64, 93–113 (2005)

    Article  Google Scholar 

  10. Subasi: Epileptic seizure detection using dynamic wavelet network. Expert System with applications 29, 343–355 (2005)

    Google Scholar 

  11. Kemal Kiymik, M., Guler, Í., Dizibuyuk, A., Akin, M.: Comparison of STFT and Wavelet Transform Methods in Determining Epileptic Seizure Activity in EEG Signals for real-time application. Computers in Biology and Medicine 35, 603–616 (2005)

    Article  Google Scholar 

  12. Ouyang, G., Li, X., Li, Y., Guan, X.: Application of wavelet-based similarity analysis to epileptic seizures prediction. Computers in Biology and medicine 37, 430–437 (2007)

    Article  Google Scholar 

  13. Freiburger Zentrum fur Datenanalyse und mollbildung, http://www.fdm.uni-freiburg.de/groups/timeseries/epi/EEGData/download/infos.txt

  14. Le Van Quyen, M., Amor, F., Rudrauf, D.: Exploring the dynamics of collective synchronizations in large ensembles of brain signals. J. Physiol. (in press, 2007)

    Google Scholar 

  15. The Mathworks, Inc.

    Google Scholar 

  16. Merkwirth, C., Parlitz, U., Wedekind, I., Lauterborn, W.: TSTOOL User Manual, Version 1.11, http://www.dpi.physik.uni-goettingen.de/tstool/HTML/index.html

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Véra Kůrková Roman Neruda Jan Koutník

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© 2008 Springer-Verlag Berlin Heidelberg

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Dourado, A., Martins, R., Duarte, J., Direito, B. (2008). Towards Personalized Neural Networks for Epileptic Seizure Prediction. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_50

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  • DOI: https://doi.org/10.1007/978-3-540-87559-8_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87558-1

  • Online ISBN: 978-3-540-87559-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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