Detection of epileptic seizures using chaotic and statistical features in the EMD domain

Proceedings - 2011 Annual IEEE India Conference: Engineering Sustainable Solutions, INDICON-2011

Volumn , Issue , 2011, Pages

  Alam, S M Shafiul ^a   Bhuiyan, M I H ^a  

^a BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Bangladesh)

Author keywords

chaotic analysis; Electro encephalogram (EEG); empirical mode decomposition (EMD); epileptic seizures; statistical analysis

Indexed keywords

APPROXIMATE ENTROPY; ARTIFICIAL NEURAL NETWORK; CHAOTIC ANALYSIS; CORRELATION DIMENSIONS; EEG SIGNALS; ELECTRO-ENCEPHALOGRAM (EEG); ELECTROENCEPHALOGRAM SIGNALS; EMPIRICAL MODE DECOMPOSITION; EPILEPTIC SEIZURES; INTRINSIC MODE FUNCTIONS; LARGEST LYAPUNOV EXPONENT; SEIZURE DETECTION; STATISTICAL FEATURES;

ELECTROENCEPHALOGRAPHY; NEURAL NETWORKS; STATISTICAL METHODS;

SIGNAL DETECTION;

EID: 84857227883     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INDCON.2011.6139341     Document Type: Conference Paper

References (11)

1. World Health Organization, "Fact sheet on epilepsy", January 2009, [Online]. Available: http://www.who.int/mediacentre/factsheets/fs999/
2. H. Adeli, S. Ghosh-Dastidar, and N. Dadmehr, "A Wavelet-Chaos Methodology for Analysis of EEGs and EEG Sub-bands to Detect Seizure and Epilepsy", IEEE Trans. on Biomedical Engineering, vol. 54, no. 2, pp. 205-211, Feb. 2007. (Pubitemid 46188163)
3. S. F. Liang, H. C. Wang, and W. L. Chang, "Combination of EEG Complexity and Spectral Analysis for Epilepsy Diagnosis and Seizure Detection", EURASIP Journal on Advances in Signal Processing, vol. 2010, article id. 853434, Hindawi Publishing Corporation.
4. M. Bedeeuzzaman V., O. Farooq and Y. U. Khan, "Automatic Seizure Detection Using Higher Order Moments", Proc. of Intl. Conf. on Recent Trends in Info., Telecomm. and Comput., pp. 159-163, March, 2010.
5. T. Fathima, Y. U. Khan, M. Bedeeuzzaman and O. Farooq, "Discriminant Analysis for Epileptic Seizure Detection", Proc. of Intl. Conf. on Devices and Communications, Feb., 2011.
6. A. T. Tzallas, M. G. Tsipouras, and D. I. Fotiadis, "Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks", Computational Intelligence and Neuroscience, vol. 2007, article id. 80510, Hindawi Publishing Corporation.
7. A. T. Tzallas, M. G. Tsipouras, and D.I. Fotiadis, "Epileptic Seizure Detection in EEGs Using Time-Frequency Analysis", IEEE Trans. on Information Technology in Biomedicine, vol. 13, no. 5, pp. 703-710, Sept. 2009.
8. R. B. Pachori, "Discrimination between Ictal and Seizure-Free EEG Signals Using Empirical Mode Decomposition", Research Letters in Signal Processing, vol. 2008, article id. 293056, Hindawi Publishing Corporation.
9. rd Intl. Conf. on Signal Acquisition and Processing, vol. 1, pp. 231-235, Feb., 2011.
10. N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proc. of R. Soc. London, Ser. A, vol. 454, no. 1971, pp. 903-995, 1998.
11. R. G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David, and C. E. Elger, "Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state", Phys. Rev. E. vol. 64, no. 6, pp. 1-8, 2001.