INSTITUT FÜR INFORMATIK Entwurf und Implementierung - Ludwig ...

Abstract
The unexpected occurrence of epileptic seizures poses a dangerous threat to patients.
A reliable prediction of epileptic seizures could oer novel treatment strategies for the
disease epilepsy. To this aim, several algorithms have been developed during the past
years, which are based on methods originating from Nonlinear Dynamics. Specic
information is extracted from brain currents to enable a prediction and subsequent
prevention of seizures [1].
To evaluate seizure prediction methods they have to be applied and analyzed systematically.
The central challenge of this diploma thesis is the design and implementation
of a software framework for this purpose, in accordance with the specic requirements
of seizure prediction. The developed software is characterized by its exibility and
modular structure. It enables usage of various parameters to control important prediction
details. In addition to some already implemented techniques, appropriate
interfaces were designed for the integration of novel seizure prediction methods.
Long-term continuous electroencephalographic measurements of epilepsy patients can
be utilized by the software for the assessment and statistical evaluation of seizure prediction
methods. Robust data processing is of particular importance. The developed
online prediction system allows manifold experiments to examine future applications
of seizure prediction.