Journal of Automation and Information Sciences

ISSN for PRINT: 1064-2315

For Online Access

Best Paper Award Selection - Editorial Board Site

2004, Volume36

Issue 8

70 pages

DOI: 10.1615/JAutomatInfScien.v36.i8

Issue price - $221.00

Tatyana I. Aksenova
Zhozef Fourier University, Grenoble, France

Vladimir V. Volkovich
International Research and Training Center of Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

Alexandro Villa
Institute of Physiology of Lausanne University, Switzerland

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.

DOI: 10.1615/JAutomatInfScien.v36.i8.30 Download article, 35-45 pages

Article price - $35.00

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