- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Recently Accepted Articles ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 847686, 11 pages
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum
1Biomedical Engineering Department, nternational University of Vietnam National Universities, Ho Chi Minh City, Vietnam
2Faculty of Applied Science, University of Technology of Vietnam National Universities, Ho Chi Minh City, Vietnam
Received 30 September 2011; Accepted 28 November 2011
Academic Editor: Carlo Cattani
Copyright © 2012 Truong Quang Dang Khoa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- S. Sanei and J. A. Chambers, EEG Signal Processing, John Wiley & Son, New York, NY, USA, 2007.
- J. Gotman and L. Y. Wang, “State-dependent spike detection: concepts and preliminary results,” Electroencephalography and Clinical Neurophysiology, vol. 79, no. 1, pp. 11–19, 1991.
- A. A. Dingle, R. D. Jones, G. J. Carroll, and W. R. Fright, “A multistage system to detect epileptiform activity in the EEG,” IEEE Transactions on Biomedical Engineering, vol. 40, no. 12, pp. 1260–1268, 1993.
- J. R. Glover Jr., P. Y. Ktonas, N. Raghavan, J. M. Urunuela, S. S. Velamuri, and E. L. Reilly, “A multichannel signal processor for the detection of epileptogenic sharp transients in the EEG,” IEEE Transactions on Biomedical Engineering, vol. 33, no. 12, pp. 1121–1128, 1986.
- J. R. Glover Jr., N. Raghavan, P. Y. Ktonas, and J. D. Frost, “Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives,” IEEE Transactions on Biomedical Engineering, vol. 36, no. 5, pp. 519–527, 1989.
- W. R. S. Webber, B. Litt, K. Wilson, and R. P. Lesser, “Practical detection of epileptiform discharges (EDs) in the EEG using an artificial neural network: a comparison of raw and parameterized EEG data,” Electroencephalography and Clinical Neurophysiology, vol. 91, no. 3, pp. 194–204, 1994.
- C. Kurth, F. Gllliam, and B. J. Steinhoff, “EEG spike detection with a Kohonen feature map,” Annals of Biomedical Engineering, vol. 28, no. 11, pp. 1362–1369, 2000.
- J. Zhu and D. Jiang, “A linear epileptic seizure predictor based on slow waves of scalp EEGs,” in Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society (IEEE-EMBS '05), pp. 7277–7280, September 2005.
- Z. Nenadic and J. W. Burdick, “Spike detection using the continuous wavelet transform,” IEEE Transactions on Biomedical Engineering, vol. 52, no. 1, pp. 74–87, 2005.
- D. E. Lerner, “Monitoring changing dynamics with correlation integrals: case study of an epileptic seizure,” Physica D, vol. 97, no. 4, pp. 563–576, 1996.
- M. Le Van Quyen, J. Martinerie, M. Baulac, and F. Varela, “Anticipating epileptic seizures in real time by a non-linear analysis of similarity between EEG recordings,” NeuroReport, vol. 10, no. 10, pp. 2149–2155, 1999.
- M. Le Van Quyen, C. Adam, J. Martinerie, M. Baulac, S. Clémenceau, and F. Varela, “Spatio-temporal characterizations of non-linear changes in intracranial activities prior to human temporal lobe seizures,” European Journal of Neuroscience, vol. 12, no. 6, pp. 2124–2134, 2000.
- M. Le Van Quyen, J. Martinerie, V. Navarro et al., “Anticipation of epileptic seizures from standard EEG recordings,” The Lancet, vol. 357, no. 9251, pp. 183–188, 2001.
- K. K. Jerger, S. L. Weinstein, T. Sauer, and S. J. Schiff, “Multivariate linear discrimination of seizures,” Clinical Neurophysiology, vol. 116, no. 3, pp. 545–551, 2005.
- C. C. Jouny, P. J. Franaszczuk, and G. K. Bergey, “Signal complexity and synchrony of epileptic seizures: is there an identifiable preictal period?” Clinical Neurophysiology, vol. 116, no. 3, pp. 552–558, 2005.
- R. Esteller, J. Echauz, M. D'Alessandro et al., “Continuous energy variation during the seizure cycle: towards an on-line accumulated energy,” Clinical Neurophysiology, vol. 116, no. 3, pp. 517–526, 2005.
- M. A. F. Harrison, M. G. Frei, and I. Osorio, “Accumulated energy revisited,” Clinical Neurophysiology, vol. 116, no. 3, pp. 527–531, 2005.
- L. D. Iasemidis, H. P. Zaveri, J. C. Sackellares, and W. J. Williams, “Linear and nonlinear modeling of ecog in temporal lobe epilepsy,” in Proceedings of the 5th Annual Rocky ountains Bioengineering Symposium, pp. 187–193, 1988.
- L. D. Iasemidis and J. C. Sackellares, “The temporal evolution of the largest lyapunov exponent on the human epileptic cortex,” in Measuring Chaos in the Human Brain, D. W. Duke and W. S. Pritchard , Eds., World Scientific, Singapore, 1991.
- L. D. Iasemidis, J. C. Principle, and J. C. Sackellares, “Measurement and quantification of spatiotemporal dynamics of human epileptic seizures,” in Nonlinear Biomedical Signal Processing, M. Akay, Ed., pp. 296–318, IEEE Press, New York, NY, USA, 2000.
- L. M. Hively, V. A. Protopopescu, and P. C. Gailey, “Timely detection of dynamical change in scalp EEG signals,” Chaos, vol. 10, no. 4, pp. 864–875, 2000.
- L. M. Hively and V. A. Protopopescu, “Channel-consistent forewarning of epileptic events from scalp EEG,” IEEE Transactions on Bio-Medical Engineering, vol. 50, no. 5, pp. 584–593, 2003.
- L. D. Iasemidis, J. C. Principe, J. M. Czaplewski, R. L. Gilmore, S. N. Roper, and J. C. Sackellares, “Spatiotemporal transition to epileptic seizures: a nonlinear dynamical analysis of scalp and intracranial eeg recordings,” in Spatiotemporal Models in Biological and Artificial Systems, F. Silva, J. C. Principe, and L. B. Almeida, Eds., pp. 81–88, IOS Press, Amsterdam, The Netherlands, 1997.
- M. Ungureanu, C. Bigan, R. Strungaru, and V. Lazarescu, “Independent component analysis applied in biomedical signal processing,” Measurement Science Review, vol. 4, section 2, 2004.
- A. Hyvärinen and E. Oja, Independent Component Analysis: Algorithms and Applications, Neural Networks Research Centre, 2000.
- J. C. Sackellares, L. D. Iasemidis, D. S. Shiau, R. L. Gilmore, and S. N. Roper, “Detection of the preictal transition from scalp eeg recordings,” Epilepsia, vol. 40, supplement 7, p. 176, 1999.
- A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano, “Determining Lyapunov exponents from a time series,” Physica D, vol. 16, no. 3, pp. 285–317, 1985.
- J. P. Eckmann, S. O. Kamphorst, D. Ruelle, and S. Ciliberto, “Liapunov exponents from time series,” Physical Review A, vol. 34, no. 6, pp. 4971–4979, 1986.
- R. Brown, P. Bryant, and H. D. I. Abarbanel, “Computing the Lyapunov spectrum of a dynamical system from an observed time series,” Physical Review A, vol. 43, no. 6, pp. 2787–2806, 1991.
- M. T. Rosenstein, J. J. Collins, and C. J. De Luca, “A practical method for calculating largest Lyapunov exponents from small data sets,” Physica D, vol. 65, no. 1-2, pp. 117–134, 1993.
- S. Sato, M. Sano, and Y. Sawada, “Practical methods of measuring the generalized dimension and the largest Lyapunov exponent in high dimensional chaotic systems,” Progress of Theoretical Physics, vol. 77, no. 1, pp. 1–5, 1987.
- M. Sano and Y. Sawada, “Measurement of the lyapunov spectrum from a chaotic time series,” Physical Review Letters, vol. 55, no. 10, pp. 1082–1085, 1985.
- P. M. Pardalos, V. A. Yatsenko, A. Messo, A. Chinchuluun, and P. Xanthopoulos, “An optimization approach for finding a spectrum of Lyapunov exponents,” Computational Neuroscience, vol. 38, part 3, pp. 285–303, 2010.