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Measure profile surrogates: A method to validate the performance of epileptic seizure prediction Thomas Kreuz,1,2,
 

Summary: Measure profile surrogates: A method to validate the performance of epileptic seizure prediction
algorithms
Thomas Kreuz,1,2,
* Ralph G. Andrzejak,1
Florian Mormann,2
Alexander Kraskov,1
Harald Stögbauer,1
Christian E. Elger,2
Klaus Lehnertz,2
and Peter Grassberger1
1
John-von-Neumann Institute for Computing, Forschungszentrum Jülich, 52425 Jülich Germany
2
Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn, Germany
(Received 21 August 2003; published 15 June 2004)
In a growing number of publications it is claimed that epileptic seizures can be predicted by analyzing the
electroencephalogram (EEG) with different characterizing measures. However, many of these studies suffer
from a severe lack of statistical validation. Only rarely are results passed to a statistical test and verified against
some null hypothesis H0 in order to quantify their significance. In this paper we propose a method to statisti-
cally validate the performance of measures used to predict epileptic seizures. From measure profiles rendered

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences