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Computational and Mathematical Methods in Medicine
Volume 2012, Article ID 847686, 11 pages
Research Article

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.


One of the inherent weaknesses of the EEG signal processing is noises and artifacts. To overcome it, some methods for prediction of epilepsy recently reported in the literature are based on the evaluation of chaotic behavior of intracranial electroencephalographic (EEG) recordings. These methods reduced noises, but they were hazardous to patients. In this study, we propose using Lyapunov spectrum to filter noise and detect epilepsy on scalp EEG signals only. We determined that the Lyapunov spectrum can be considered as the most expected method to evaluate chaotic behavior of scalp EEG recordings and to be robust within noises. Obtained results are compared to the independent component analysis (ICA) and largest Lyapunov exponent. The results of detecting epilepsy are compared to diagnosis from medical doctors in case of typical general epilepsy.