On prediction of epileptic seizures by means of genetic programming artificial features

Annals of Biomedical Engineering

Volumn 34, Issue 3, 2006, Pages 515-529

  Firpi, Hiram ^a,d   Goodman, Erik ^b   Echauz, Javier ^c  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b Michigan State University   (United States)

^c BioQuantix Corp   (United States)

^d GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Artificial feature; Epilepsy; Feature extraction; Genetic programming; Seizure prediction; State space reconstruction

Indexed keywords

ARTIFICIAL FEATURES; EPILEPSY; GENETIC PROGRAMMING; SEIZURE PREDICTIONS; STATE-SPACE RECONSTRUCTIONS;

ALGORITHMS; BIOMEDICAL ENGINEERING; COMPUTER PROGRAMMING; DISEASES; ELECTROENCEPHALOGRAPHY; PATIENT MONITORING;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ELECTROENCEPHALOGRAPHY; EPILEPSY; FEMALE; HUMAN; MALE; PREDICTION AND FORECASTING; SIGNAL PROCESSING; TIME;

ALGORITHMS; ELECTROENCEPHALOGRAPHY; EPILEPSY; FEMALE; HUMANS; MALE; PREDICTIVE VALUE OF TESTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 33646431417     PISSN: 00906964     EISSN: 15739686     Source Type: Journal    
DOI: 10.1007/s10439-005-9039-7     Document Type: Article

References (26)

1. D'Alessandro, M. The Utility of Intracranial EEG Feature and Channel Synergy for Evaluating the Spatial and Temporal Behavior of Seizure Precursors, PhD Dissertation, Georgia Institute of Technology, Atlanta, 2001.
2. D'Alessandro, M., R. Esteller, G. Vachtsevanos. A. Hinson, J. Echauz, and B. Litt. Epileptic seizures prediction using hybrid feature selection over multiple intracranial EEG electrode contacts: A report of four patients. IEEE Trans. Biomed. Eng. 50(5):603-615, 2003.
3. Duda, R., P. Hart, and D. Stork. Pattern Classification, 2nd ed. New York: Wiley, 2001.
4. Echauz, J. Wavelet Neural Networks for EEG Modeling and Classification, PhD Dissertation, Georgia Institute of Technology, August 1995.
5. Elger, C. E., and K. Lehnertz. Seizure prediction by non-linear time series analysis of brain electrical activity. Eur. J. Neurosci. 10:786-789, 1998.
6. Firpi, H. Genetically Found, Neurally Computed Artificial Features with Applications to Epileptic Seizure Detection and Prediction, Master's Thesis, University of Puerto Rico-Mayagüez, 2001.
7. Firpi, H. On Prediction and Detection of Epileptic Seizures by Means of Genetic Programming Artificial Features, PhD Dissertation, Michigan State University, 2005.
8. Gilmore, R., and M. Lefranc. The Topology of Chaos: Alice in the Stretch and Squeezeland. New York: Wiley, 2002.
9. Haupt, R. L., and S. E. Haupt. Practical Genetic Algorithms. New York: Wiley, 1998.
10. Iasemidis, L. Epileptic seizure prediction and control. IEEE Trans. Biomed. Eng. 50(5):549-559, 2003.
11. Iasemidis, L., D.-S. Shiau, W. Chaovalitwongse, J. C. Sackellares, P. M. Pardalos, J. C. Principe, P. R. Carney, A. P. Prasad, B. Veeramani, and K. Tsakalis. Adaptive epileptic seizure prediction system. IEEE Trans. Biomed. Eng. 50(5):616-627, 2003.
12. Jansen, B. H. Quantitative analysis of electroencephalograms: Is there chaos in the future? Int. J. Biomed. Comput. 27:95-123, 1991.
13. Jia, W., N. Kong, F. Li, X. Gao, S. Gao, G. Zhang, Y. Wang, and F. Yang. An epileptic seizure prediction algorithm based on second-order complexity measure. Physiol. Meas. 26:609-625, 2005.
14. Koza, J. R. Genetic Programming: On Programming of Computers by Means of Natural Selection. Cambridge, MA: MIT Press, 1992.
15. Lee, S. A., D. D. Spencer, and S. S. Spencer. Intracranial EEG seizure-onset patterns in neocortical epilepsy. Epilepsia 41(3):297-307, 2000.
16. Lehnertz, K., and C. E. Elger. Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss. Electroencephalogr Clin Neurophysiol 95:108-117.
17. Lehnertz, K., and B. Litt. The First International Collaborative Workshop on Seizure Prediction: Summary and data description. Clin. Neurophysiol. 116(3):493-505, 2005.
18. Litt, B., R. Esteller, J. Echauz, M. D'Alessandro, R. Shor, T. Henry, P. Pennell, C. Epstein, R. Bakay, M. Dichter, and G. Vachtsevanos. Epileptic seizures may begin hours in advance of clinical seizures: A report of five patients. Neuron 29(4):51-64, 2001.
19. Martinerie, J., C. Adam, M. le van Quyen, M. Baulac, S. Clemenceau, B. Renault, and F. J. Valera. Epileptic seizures can be anticipated by non-linear analysis. Nat. Med. 4:1176-1176, 1998.
20. Niederhoefer, C., F. Gollas, A. Chernihovskyi, K. Lehnertz, and R. Tetzlaff. Detection of seizure precursors in the EEG with cellular neural networks. Epilepsia 45(7):245, 2004 (abstract).
21. Orfanidis, S. J. Optimum Signal Processing: An Introduction, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1996.
22. Petrosian, A., D. Prokhorov, R. Homan, R. Dashieff, and D. Wunch. Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG. Neurocomputing 30:201-218, 2000.
23. Pritchard, W. S., and D. W. Duke. Measuring chaos in the brain: A tutorial review of nonlinear dynamical EEG analysis. Brain Cogn 27(3):353-397, 1995.
24. Sowa, R., F. Mormann, A. Chernihovskyi, C. Niederhoefer, R. Tetzlaff, C. Elger, and K. Lehnertz. Seizure prediction: Measuring EEG phase synchronization with cellular neural networks. Epilepsia 45(7):244, 2004 (abstract).
25. Sprott, J. C. Chaos and Time-Series Analysis. New York: Oxford University Press, 2003.
26. Takens, F. Detecting strange attractors in turbulence. In: Dynamical Systems and Turbulence, Warwick 1980 Lecture Notes in Mathematics 898. Berlin: Springer-Verlag, 1981, pp. 336-381.