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Research Abstracts Online
January - December 2011

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University of Minnesota Twin Cities
College of Science and Engineering
Department of Biomedical Engineering

PI: Theoden Netoff

Seizure Prediction With EEG

These researchers seek to design and validate reliable frameworks for epileptic seizure prediction with electrocorticogram (ECoG) and intracranial electroencephalogram (iEEG). The ultimate goal of this research is to develop an implantable device for the seizure prediction and thus this dissertation specifically focuses on developing and validating algorithms for seizure prediction with ECoG/iEEG that can be employed in an implantable device with high sensitivity and specificity. In contrast to previous works, most of which focused on nonlinear measurements, the proposed algorithms use only linear features of ECoG/iEEG and this approach allows the algorithms to be more favorable to being used in an implantable device. The researchers have proposed a new patient-specific seizure prediction algorithm with ECoG/iEEG. It is novel in sense that only a set of spectral power features of ECoG/iEEG are extracted and that predictive models have been established and validated through the classification of cost-sensitive support vector machines (SVMs) and the double cross-validation method. The proposed algorithm has been evaluated over 433.2 interictal recordings with 80 seizure events from 18 human epileptics in the Freiburg Database and it has achieved high sensitivity of 97.5%, a low false alarm rate of 0.27 per hour, and total false prediction times of 13.0%. The researchers are further developing the reduced-complexity algorithm that uses linear classifiers and a certain number of features, by substituting the nonlinear SVMs with linear ones and investigating a set of key features.

Group Members

Bryce C. Beverlin, Graduate Student
Michael J. Brown, Graduate Student
Samuel W. Check, Undergraduate Student
Abby Beuning Holt, Collaborator
Oscar Miranda Dominguez, Graduate Student
Brendan Murphy, Undergraduate Student
Yun Sang Park, Graduate Student
Tyler Stigen, Graduate Student