WIT Press

Relation Between Singular Values And Graph Dimensions Of Deterministic Epileptiform EEG Signals

Price

Free (open access)

Paper DOI

10.2495/BIO950631

Volume

2

Pages

8

Published

1995

Size

863 kb

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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