Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum | Zendy

Truong Quang Dang Khoa | Zendy; Huong Minh Nguyen | Zendy; Vo Van Toi | Zendy

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Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum

Author(s) -

Truong Quang Dang Khoa,

Huong Minh Nguyen,

Vo Van Toi

Publication year - 2012

Publication title -

computational and mathematical methods in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.462

H-Index - 48

eISSN - 1748-6718

pISSN - 1748-670X

DOI - 10.1155/2012/847686

Subject(s) - electroencephalography , epilepsy , scalp , lyapunov exponent , computer science , chaotic , pattern recognition (psychology) , noise (video) , filter (signal processing) , lyapunov function , artificial intelligence , speech recognition , neuroscience , medicine , psychology , computer vision , nonlinear system , physics , surgery , quantum mechanics , image (mathematics)

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.

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