Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum
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 red...
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doaj-f85715dc9e7944eea4f0212ac7ac953c2020-11-25T00:04:46ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182012-01-01201210.1155/2012/847686847686Detecting Epileptic Seizure from Scalp EEG Using Lyapunov SpectrumTruong Quang Dang Khoa0Nguyen Thi Minh Huong1Vo Van Toi2Biomedical Engineering Department, nternational University of Vietnam National Universities, Ho Chi Minh City, VietnamFaculty of Applied Science, University of Technology of Vietnam National Universities, Ho Chi Minh City, VietnamBiomedical Engineering Department, nternational University of Vietnam National Universities, Ho Chi Minh City, VietnamOne 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.http://dx.doi.org/10.1155/2012/847686 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Truong Quang Dang Khoa Nguyen Thi Minh Huong Vo Van Toi |
spellingShingle |
Truong Quang Dang Khoa Nguyen Thi Minh Huong Vo Van Toi Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum Computational and Mathematical Methods in Medicine |
author_facet |
Truong Quang Dang Khoa Nguyen Thi Minh Huong Vo Van Toi |
author_sort |
Truong Quang Dang Khoa |
title |
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum |
title_short |
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum |
title_full |
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum |
title_fullStr |
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum |
title_full_unstemmed |
Detecting Epileptic Seizure from Scalp EEG Using Lyapunov Spectrum |
title_sort |
detecting epileptic seizure from scalp eeg using lyapunov spectrum |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2012-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2012/847686 |
work_keys_str_mv |
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1725428100954587136 |