학술논문
Absence seizure epilepsy detection using linear and nonlinear eeg analysis methods
Document Type
Conference
Author
Source
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. :6333-6336 Jul, 2013
Subject
Language
ISSN
1094-687X
1558-4615
1558-4615
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.