The seizure prediction characteristic: a general framework to assess and compare seizure prediction methods.

Abstract The unpredictability of seizures is a central problem for all patients suffering from uncontrolled epilepsy. Recently, numerous methods have been suggested that claim to predict from the EEG the onset of epileptic seizures. In parallel, new therapeutic devices are in development that could control upcoming seizures provided that their onset is known in advance. A reliable clinical application controlling seizures, consisting of a seizure prediction method and an intervention system, would improve patient quality of life. The question therefore arises as to whether the performance of the seizure prediction methods is already sufficient for clinical applications. The answer requires assessment criteria to judge and compare these methods, but recognized criteria still do not exist. Based on clinical, behavioral, and statistical considerations, we suggest the “seizure prediction characteristic” to evaluate seizure prediction methods. Results of this approach are exemplified by its application to the “dynamical similarity index” seizure prediction method using 582 hours of intracranial EEG data, including 88 seizures.