학술논문
Brain dynamics based automated epileptic seizure detection
Document Type
Conference
Author
Source
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. :946-949 Aug, 2014
Subject
Language
ISSN
1094-687X
1558-4615
1558-4615
Abstract
We developed and tested a seizure detection algorithm based on two measures of nonlinear and linear dynamics, that is, the adaptive short-term maximum Lyapunov exponent (ASTL max ) and the adaptive Teager energy (ATE). The algorithm was tested on long-term (0.5–11.7 days) continuous EEG recordings from five patients (3 with intracranial and 2 with scalp EEG) with a total of 56 seizures, producing a mean sensitivity of 91% and mean specificity of 0.14 false positives per hour. The developed seizure detection algorithm is data-adaptive, training-free, and patient-independent.