Relation Between Singular Values And Graph Dimensions Of Deterministic Epileptiform EEG Signals
Price
Free (open access)
Transaction
Volume
2
Pages
8
Published
1995
Size
863 kb
Paper DOI
10.2495/BIO950631
Copyright
WIT Press
Author(s)
V. Cabukovski, N. de M. Rudolph & N. Mahmood
Abstract
Computerised detection and prediction of epileptic discharges from EEG data is a problem whose solution may lead to the prediction of epileptic seizures and planning of treatment. The recently confirmed fact that the EEG has a frac- tal nature enables a new approach to analysis of epilepsy. A conventional signal processing approach is not appropriate for highly complex signals, such as chao- tic deterministic signals including epileptiform EEG. In our previous work we found that the graph dimension is the most appropriate measure for real-time fractal dimension estimation of EEG signals, and that it could be used for differentiation between parts
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