Absence seizure epilepsy detection using linear and nonlinear eeg analysis methods

Author

Sakkalis, Vangelis ; Giannakakis, Giorgos ; Farmaki, Christina ; Mousas, Abdou ; Pediaditis, Matthew ; Vorgia, P. ; Tsiknakis, Manolis

Author_Institution

Inst. of Comput. Sci., Found. for Res. & Technol., Heraklion, Greece

fYear

2013

fDate

3-7 July 2013

Firstpage

6333

Lastpage

6336

Abstract

In this study, we investigated three measures capable of detecting absence seizures with increased sensitivity based on different underlying assumptions. Namely, an information-based method known as Approximate Entropy, a nonlinear alternative (Order Index), and a linear variance analysis approach. The results on the long-term EEG data suggest increased accuracy in absence seizure detection achieving sensitivity as high as 97.33% with no further application of any sophisticated classification scheme.

Keywords

electroencephalography; entropy; medical disorders; medical signal detection; EEG data; absence seizure epilepsy detection; approximate entropy; information-based method; linear EEG analysis; linear variance analysis; nonlinear EEG analysis; nonlinear alternative analysis; order index analysis; Accuracy; Electroencephalography; Entropy; Epilepsy; Indexes; Sensitivity; Time series analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

Conference_Location

Osaka

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2013.6611002

Filename

6611002