Epileptic seizure classification using neural networks with 14 features

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5178 LNAI, Issue PART 2, 2008, Pages 281-288

  Costa, Rui P ^a   Oliveira, Pedro ^a   Rodrigues, Guilherme ^a   Leitão, Bruno ^a   Dourado, António ^a  

^a UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

Classification; Data mining; EEG processing; Epilepsy; Neural networks; Seizure prediction

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); DATA MINING; ELECTROENCEPHALOGRAPHY; KNOWLEDGE BASED SYSTEMS; NEUROLOGY;

AUTOMATIC CLASSIFICATION SYSTEMS; CLASSIFICATION ACCURACY; ELECTROENCEPHALOGRAM SIGNALS; EPILEPSY; NEURAL NETWORKS ARCHITECTURE; NEUROLOGICAL DISORDERS; SEIZURE PREDICTION; TIME CONSUMING ANALYSIS;

NEURAL NETWORKS;

EID: 57749185429     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85565-1_35     Document Type: Conference Paper

References (14)

1. Srinivasan, V., Eswaran, C., Sriraam, N.: Approximate entropy-based epileptic EEG detection using artificial neural networks. IEEE Transactions On Information Technology In Biomedicine 11(3), 288-295 (2007)
2. Ghosh-Dastidar, S., Adeli, H., Dadmehr, N.: Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection. IEEE Transactions on Biomedical Engineering 54(7), 1545-1551 (2007)
3. Subasi, A.: Application of adaptive neuro-fuzzy inference system for epileptic seizure detection using wavelet feature extraction. Comput. Biol. Med. 37(2), 227-244 (2007)
4. Mormann, F., Andrzejak, R.G., Elger, C.E., Lehnertz, K.: Seizure prediction: the long and winding road. Brain 130, 314-333 (2007)
5. Freiburger Zentrum fur Datenanalyse und Mollbildung: The freiburg seizure prediction project database, https://epilepsy.uni-freiburg.de/freiburg-seizure- prediction-project/eeg-database
6. Leitão, B., Dourado, A., Vieira, M., Sales, F.: Computational system for the prediction of epileptic seizures through multi-sensorial information analysis. Technical report, Department of Informatics Engineering, University of Coimbra (September 2007)
7. Winterhalder, M., Schelter, B., Maiwald, T., Brandt, A., Schad, A., Schulze-Bonhage, A., Timmer, J.: Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction. Clinical Neurophysiology 117, 2399-2413 (2006)
8. Litt, B., Esteller, R., Echauz, J., D'Alessandro, M., Shor, R., Henry, T., Pennell, P., Epstein, C., Bakay, R., Dichter, M., Vachtsevanos, G.: Epileptic seizures may begin hours in advance of clinical onset: A report of five patients. Neuron. 30(1), 51-64 (2001)
9. Merkwirth, C., Parlitz, U., Wedekind, I., Lauterborn, W.: Tstool user manual, version 1.11 (2001), http://www.dpi.physik.uni-goettingen.de/tstool/ HTML/index.html
10. Demuth, H., Beale, M., Hagan, M.: Neural network toolbox 6 user's guide. The MathWorks (2008)
11. Chen, S., Cowan, C., Grant, P.M.: Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on Neural Networks 2(2), 302-309 (1991)
12. Hagan, M.T., Demuth, H.B., Beale, M.: Neural Network Design. PWS Publishing Company (1996)
13. Elman, J.L.: Finding structure in time. Cognitive Science 14, 179-211 (1990)
14. Waibel, A., Hanazawa, T., Hinton, G., Shikano, K., Lang, K.: Phoneme recognition using time-delay neural networks. IEEE Transactions on Acoustics, Speech and Signal Processing 37(3), 328-339 (1989)