Skip to main content

2016 | OriginalPaper | Buchkapitel

5. A Novel Clustering Technique for the Detection of Epileptic Seizures

verfasst von : Siuly Siuly, Yan Li, Yanchun Zhang

Erschienen in: EEG Signal Analysis and Classification

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter presents a different clustering technique for detecting epileptic seizures from EEG signals. This algorithm uses all the data points of every EEG signal. This algorithm uses all the data points of every EEG signal and reduces computational complexicity.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Abdulkadir, S. (2009) ‘Multiclass least-square support vector machines for analog modulation classification’, Expert System with Applications, Vol. 36, pp. 6681–6685. Abdulkadir, S. (2009) ‘Multiclass least-square support vector machines for analog modulation classification’, Expert System with Applications, Vol. 36, pp. 6681–6685.
Zurück zum Zitat Andrzejak, R.G., Lehnertz, K., Mormann, F., Rieke, C., David, P., and Elger, C. E. (2001) ‘Indication of Non Linear Deterministic and Finite-Dimensional Structures in Time Series of Brain Electrical Activity: Dependence on Recording Region and Brain State’, Physical Review E, Vol. 64, 061907. Andrzejak, R.G., Lehnertz, K., Mormann, F., Rieke, C., David, P., and Elger, C. E. (2001) ‘Indication of Non Linear Deterministic and Finite-Dimensional Structures in Time Series of Brain Electrical Activity: Dependence on Recording Region and Brain State’, Physical Review E, Vol. 64, 061907.
Zurück zum Zitat Blankertz, B., Muller, K..R., Krusienki, D. J., Schalk, G., Wolpaw, J.R., Schlogl, A., Pfurtscheller, S., Millan, J. De. R., Shrooder, M. and Birbamer, N. (2006) ‘The BCI competition III: validating alternative approaches to actual BCI problems’, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 14, no. 2, pp. 153–159. Blankertz, B., Muller, K..R., Krusienki, D. J., Schalk, G., Wolpaw, J.R., Schlogl, A., Pfurtscheller, S., Millan, J. De. R., Shrooder, M. and Birbamer, N. (2006) ‘The BCI competition III: validating alternative approaches to actual BCI problems’, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 14, no. 2, pp. 153–159.
Zurück zum Zitat Chandaka, S., Chatterjee, A. and Munshi, S. (2009) ‘Cross-correlation aided support vector machine classifier for classification of EEG signals’, Expert System with Applications, Vol. 36, pp. 1329–1336. Chandaka, S., Chatterjee, A. and Munshi, S. (2009) ‘Cross-correlation aided support vector machine classifier for classification of EEG signals’, Expert System with Applications, Vol. 36, pp. 1329–1336.
Zurück zum Zitat Guo, L., Rivero, D., Seoane, J.A. and Pazos, A. (2009) ‘Classification of EEG signals using relative wavelet energy and artificial neural networks’, GCE, pp. 12–14. Guo, L., Rivero, D., Seoane, J.A. and Pazos, A. (2009) ‘Classification of EEG signals using relative wavelet energy and artificial neural networks’, GCE, pp. 12–14.
Zurück zum Zitat Jahankhani, P., Kodogiannis, V. and Revett, K. (2006) ‘EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks’, IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA’06). Jahankhani, P., Kodogiannis, V. and Revett, K. (2006) ‘EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks’, IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA’06).
Zurück zum Zitat Kang, H., Nam, Y. and Choi, S. (2009) ‘Composite common spatial pattern for subject-to-subject transfer’, IEEE Signal Processing letters, Vol. 16, no. 8, pp. 683–686. Kang, H., Nam, Y. and Choi, S. (2009) ‘Composite common spatial pattern for subject-to-subject transfer’, IEEE Signal Processing letters, Vol. 16, no. 8, pp. 683–686.
Zurück zum Zitat Lotte, F. and Guan, C. (2010) ‘Spatially regularized common spatial patterns for EEG classification’, Inria-00447435 (25 Jan 2010) version 2. Lotte, F. and Guan, C. (2010) ‘Spatially regularized common spatial patterns for EEG classification’, Inria-00447435 (25 Jan 2010) version 2.
Zurück zum Zitat Lu, H., Plataniotis, K.N. and Venetsanopoulos, A.N. (2009) ‘Regularized common spatial patterns with generic learning for EEG signal classification’, 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, September 2–6, 2009, pp. 6599–6602. Lu, H., Plataniotis, K.N. and Venetsanopoulos, A.N. (2009) ‘Regularized common spatial patterns with generic learning for EEG signal classification’, 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, September 2–6, 2009, pp. 6599–6602.
Zurück zum Zitat Polat, K. and Gunes, S. (2007) ‘Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform’, Applied Mathematics and Computation, 187 1017–1026. Polat, K. and Gunes, S. (2007) ‘Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform’, Applied Mathematics and Computation, 187 1017–1026.
Zurück zum Zitat Siuly, Y. Li, and P. Wen, (2011a) ‘EEG signal classification based on simple random sampling technique with least square support vector machines’, International journal of Biomedical Engineering and Technology, Vol. 7, no. 4, pp. 390–409. Siuly, Y. Li, and P. Wen, (2011a) ‘EEG signal classification based on simple random sampling technique with least square support vector machines’, International journal of Biomedical Engineering and Technology, Vol. 7, no. 4, pp. 390–409.
Zurück zum Zitat Siuly, Y. Li, and P. Wen, (2011b) ‘Clustering technique-based least square support vector machine for EEG signal classification’, Computer Methods and Programs in Biomedicine, Vol. 104, no. 3, pp. 358–372. Siuly, Y. Li, and P. Wen, (2011b) ‘Clustering technique-based least square support vector machine for EEG signal classification’, Computer Methods and Programs in Biomedicine, Vol. 104, no. 3, pp. 358–372.
Zurück zum Zitat Subasi, A. (2007) ‘EEG signal classification using wavelet feature extraction and a mixture of expert model’, Expert System with Applications, Vol. 32, pp. 1084–1093. Subasi, A. (2007) ‘EEG signal classification using wavelet feature extraction and a mixture of expert model’, Expert System with Applications, Vol. 32, pp. 1084–1093.
Zurück zum Zitat Ubeyli, E.D. (2010) ‘Least Square Support Vector Machine Employing Model-Based Methods coefficients for Analysis of EEG Signals’, Expert System with Applications. 37 233–239. Ubeyli, E.D. (2010) ‘Least Square Support Vector Machine Employing Model-Based Methods coefficients for Analysis of EEG Signals’, Expert System with Applications. 37 233–239.
Zurück zum Zitat Yong, X, Ward, R.K. and Birch, G.E. (2008) ‘Sparse spatial filter optimization for EEG channel reduction in brain-computer interface’, ICASSP 2008, pp. 417–420. Yong, X, Ward, R.K. and Birch, G.E. (2008) ‘Sparse spatial filter optimization for EEG channel reduction in brain-computer interface’, ICASSP 2008, pp. 417–420.
Metadaten
Titel
A Novel Clustering Technique for the Detection of Epileptic Seizures
verfasst von
Siuly Siuly
Yan Li
Yanchun Zhang
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-47653-7_5

Neuer Inhalt