Nonparametric On-Line Detection of Changes in Signal Spectral Characteristics for Early Prediction of Epilepsy Seizure Onset

Details

Serval ID
serval:BIB_36134
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Nonparametric On-Line Detection of Changes in Signal Spectral Characteristics for Early Prediction of Epilepsy Seizure Onset
Journal
Journal of Automation and Information Sciences
Author(s)
Aksenova T.I., Volkovich V.V., Villa A.E.P.
ISSN
1064-2315
Publication state
Published
Issued date
2004
Volume
36
Number
8
Pages
35-45
Language
english
Abstract
The present study introduces the method for solving the problem on early prediction of epilepsy seizure onset based on analysis of multi-channel electroencephalogram (EEG). This problem is considered as the problem of on-line detection of multiple abrupt changes in spectral characteristics of the process under consideration. With EEG characteristics not being changed abruptly, to describe growing changes the use was made of multiple disharmony model. The quantity to characterize the degree of spectral instability is applied as a detector. The nonparametric sequential method of detecting disharmony is realized in computational algorithms effective enough to be used in real time for 32-channel EEG and to open possibilities for creating the system of automatic prediction.
Create date
19/11/2007 11:10
Last modification date
20/08/2019 14:23
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