A signal regularity-based automated seizure prediction algorithm using long-term scalp EEG recordings
The purpose of this study was to evaluate a signal regularity-based automated seizure prediction algorithm for scalp EEG. Signal regularity was quantified using the Pattern Match Regularity Statistic (PMRS), a statistical measure. The primary feature of the prediction algorithm is the degree of conv...
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| Date: | 2011 |
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| Main Authors: | , , , , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Інститут кібернетики ім. В.М. Глушкова НАН України
2011
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| Series: | Кибернетика и системный анализ |
| Subjects: | |
| Online Access: | http://dspace.nbuv.gov.ua/handle/123456789/84219 |
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| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | A signal regularity-based automated seizure prediction algorithm using long-term scalp EEG recordings / Ch. Jui-Hong, Sh. Deng-Shan, J.J. Halford, K.M. Kelly, R.T. Kern, M.C.K. Yang, Zh. Jicong, J.Ch. Sackellares, P.M. Pardalos // Кибернетика и системный анализ. — 2011. — Т. 47, № 4. — С. 95-107. — Бібліогр.: 41 назв. — рос. |
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