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Title: ARMA modeling for the diagnosis of controlled epileptic activity in young children
Authors: Cassar, Tracey A.
Camilleri, Kenneth P.
Fabri, Simon G.
Zervakis, Michalis
Micheloyannis, Sifis
Keywords: Epileptic children -- Behavior modification
Issue Date: 2008
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Cassar, T. A., Camilleri, K. P., Fabri, S. G., Zervakis, M., & Micheloyannis, S. (2008, March). ARMA modeling for the diagnosis of controlled epileptic activity in young children. 3rd International Symposium on Communications, Control, and Signal Processing, ISCCSP2008, St. Julians. 25-30.
Abstract: Parametric models are widely used for EEG data analysis. In this experimental study an autoregressive moving average (ARMA) model was used to extract spectral features within defined frequency bands which were then used to discriminate a group of children with controlled mild epilepsy from an age- and sex- matched control group. This study differs from other published works in that it shows that this technique can be used as a biomarker to distinguish the epileptic subjects specifically when the EEG recordings of these subjects are clinically diagnosed as normal. Using the spectral features and a linear discriminant classifier a global classification score of up to 85% was achieved on our clinical data. Furthermore the results showed that epileptic children have significantly higher spectral power in frequency bands up to 45Hz, with the largest difference occurring within the alpha band.
Description: This work was partly supported by the European FP6 Network of Excellence BIOPATTERN, contract number 508803 and by the internal research grant of the University of Malta LBA-73-967.
Appears in Collections:Scholarly Works - FacEngSCE

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