Epileptic seizures predicted by modified particle filters

Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC

Volumn , Issue , 2008, Pages 351-356

  Liu, Derong ^a,b   Pang, Zhongyu ^a,b  

^a IEEE

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Dynamic model; Epileptic seizure; Neural networks; Particle filters; Seizure prediction

Indexed keywords

AIR FILTERS; ARTIFICIAL INTELLIGENCE; CURVE FITTING; ELECTROENCEPHALOGRAPHY; FORECASTING; FREQUENCY BANDS; LEAST SQUARES APPROXIMATIONS; NEURAL NETWORKS; NONLINEAR FILTERING; POISSON DISTRIBUTION; SIGNAL FILTERING AND PREDICTION; WAVE FILTERS; WAVELET TRANSFORMS;

AUTOREGRESSIVE PROCESSES; DYNAMIC MODEL; EEG DATA; EEG RECORDINGS; ELECTRICAL DISTURBANCES; EPILEPTIC SEIZURE; EPILEPTIC SEIZURES; GAUSSIAN; HIDDEN VARIABLES; INITIAL STATES; INTERNATIONAL CONFERENCES; MINIMUM LEAST SQUARE ERROR; MODEL PARAMETERS; PARTICLE FILTERING; PARTICLE FILTERS; PICK-UP; PREDICTION RATE; SECOND ORDERS; SEIZURE ONSET; SEIZURE PREDICTION; SPECIFIC FREQUENCIES; STOCHASTIC PROCESSING;

PARAMETER ESTIMATION;

EID: 49249121170     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNSC.2008.4525239     Document Type: Conference Paper

References (22)

1. M. S. Arulampalam, S. Maskell, N. Gordon and T. Clapp, "A tutorial on particle filters for online nonlinear non-Gaussian Bayesian tracking," IEEE Transactions on Signal Processing, vol. 50, no. 2, pp. 174-188, 2002.
2. J. Bernardo and A. Smith, Bayesian Theory, New York: Wiley, 1994.
3. S. Chatterjee and A. S. Hadi, "Influential observations, high leverage points, and outliers in linear regression," Statistical Science, vol. 1, pp. 379-393, 1986.
4. M. D'Alessandro, R. Esteller, G. Vachtsevanos, A. Hinson, J. Echauz, and B. Litt, "Epileptic seizure prediction using hybrid feature selection over multiple intracranial EEG electrode contact: A report of four patients," IEEE Trans. Biomedical Engineering, vol. 50, no. 5, pp. 603-615, 2003.
5. A. Doucet, "On sequential simulation-based methods for Bayesian filtering," Technical Report, Signal Processing Group, Univ. Cambridge, Cambridge, UK, 1998.
6. A. Doucet, N. D. Freitas, and N. Gordon, Sequential Monte Carlo Methods in Pratice, Berlin: Springer, 2001.
7. A. Doucet, S. Godsill, and C. Andrieu, "On sequential Monte Carlo sampling methods for Bayesian filtering," Statistics and Computing, vol. 10, pp. 197-208, 2000.
8. J. Geweke, "Bayesian inference in econometric models using Monte Carlo integration," Econometrica, vol. 57, pp. 1317-1339, 1989.
9. W. Gilks and C. Berzuini, "Following a moving target - Monte Carlo inference for dynamic Bayesian models," Journal of the Royal Statistical Society B, vol. 1, pp. 127-146, 2001.
10. N. J. Gordon, D. J. Salmond, and A. F. M. Smith, "Novel approach non-Gaussian Bayesian state estimation," IEE Proc. F, vol. 140, pp. 107-113, 1993.
11. L. D. Iasemidis, "Epileptic seizure prediction and control," IEEE Trans. Biomedical Engineering, vol. 50, no. 5, pp. 549-558, 2003.
12. L. D. Iasemidis and J. C. Sackellares, "The evolution with time of the spatial distribution of the largest Lyapunov exponent ont he human epileptic cortex", in Measuring Chaos in the Human Brain, F. Duke and W. Pritchard, Eds., Singapore: World Scientific, pp. 49-82, 1991.
13. L. D. Iasemidis, D. S. Shiau, W. Chaovalitwongse, J. C. Sackellares, P. M. Pardalos, J. C. Principe, P. R. Carney, A. Prasad, B. Veeramani, and K. Tsakalis, "Adaptive epileptic seizure prediction system," IEEE Trans. Biomedical Engineering, vol. 50, no. 5, pp. 616-627, 2003.
14. C. Kwok, D. Fox, and M. Meila, "Real-time particle filters," Proceedings of the IEE, vol. 92, no. 3, pp. 469-484, 2004.
15. J. R. Larcoque, J. P. Reilly, and W. Ng, "Particle filters for tracking an unknown number of sourxes," IEEE Transaction on Signal Processing, vol. 50, pp. 2926-2937, 2002.
16. K. Lehnertz and C. E. Elger, "Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss," Electroencephalographic Clinical Neurophysiology, vol. 95, pp. 108-117, 1995.
17. J. S. Liu, Monte Carlo Strategies in Scientific Computing, New York: Springer, 2001.
18. J. S. Liu and R. Chen, "Sequential Monte Carlo methods for dynamic systems," Journal of the American Statistical Association, vol. 93, pp. 1032-1044, 1998.
19. F. Mormann, R. G. Andraejak, C. E. Elger, and K. Lehneitz, "Seizure prediction: the long and winding road," Brain (Advance Acess), pp. 1-20, 2006.
20. B. Schelter, M. Winterhalder, T. Maiwald, A. Brandt, A. Schad, A. Schulze-Bonhage, and J. Timmer, "Testing statistical significance of multivariate time series analysis techniques for epileptic seizure prediction," Chaos, 16: 013108, 2006.
21. P. Suffczynski, F. H. Lopes da Silva, J. Parra, D. N. Velis, B. M. Bouwman, C. M. van Rijin, P. van Hese, P. Boon, H. Khosravani, M. Derchansky, P. Carlen, and S. Kalitzin, "Dynamics of epileptic phenomena determined from statistics of ictal transitions," IEEE Transaction on Biomedical Engineering, vol. 53, pp. 524-532, 2006.
22. J. M. Zurada, Introduction to Artificial Neural Systems, New York: West Publishing Company, 1992.