7.6: Presentation session: Poster session and reception: “Seizure prediction: One step closer. Graphical user interface for fast EEG review and statistical validation of PSDM”
Epilepsy is one of the most widely occurring and costly neurological disorders. The CDC has named developing a prediction method for seizures as its top priority in epileptic research because the unpredictability of seizures causes immense psychological stress on persons with lifetime epilepsy. In order to reduce these stresses, Hively et al have designed an algorithm to provide forewarning of epileptic events from scalp EEG data. To help in the development of this algorithm for clinical application, we have designed a graphical user interface (GUI) to allow experts to rapidly characterize electroencephalogram (EEG) datasets to be used to train the forewarning algorithm. We have also performed a statistical validation of the forewarning results to date. Both of these aspects of this project contribute to the overall goal of realizing reliable seizure prediction for people with epilepsy
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