Network-Based Techniques in EEG Data Analysis and Epileptic Brain Modeling

Oleg A. Prokopyev (), Vladimir L. Boginski (), Wanpracha Chaovalitwongse (), Panos M. Pardalos (), J. Chris Sackellares () and Paul R. Carney
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Oleg A. Prokopyev: University of Pittsburgh
Vladimir L. Boginski: Florida State University
Wanpracha Chaovalitwongse: The State University of New Jersey
Panos M. Pardalos: University of Florida
J. Chris Sackellares: University of Florida
Paul R. Carney: University of Florida

A chapter in Data Mining in Biomedicine, 2007, pp 559-573 from Springer

Abstract: Abstract We discuss a novel approach of modeling the behavior of the epileptic human brain, which utilizes network-based techniques in combination with statistical preprocessing of the electroencephalographic (EEG) data obtained from the electrodes located in different parts of the brain. In the constructed graphs, the vertices represent the “functional units” of the brain, where electrodes are located. Studying dynamical changes of the properties of these graphs provides valuable information about the patterns characterizing the behavior of the brain prior to, during, and after an epileptic seizure.

Keywords: Graph theory; data analysis; EEG data; brain; epilepsy (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-0-387-69319-4_28

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