Open M.D. Theses
Epileptic seizures are detected clinically using an Electroencephalogram (EEG). Since home-usage of such devices for early seizure onset warning is currently not possible, the aim of this work is the analysis of alternative, EEG-less methods for seizure detection or prediction.
The work of this thesis is split in four parts:
1. Analysis of existing methods for EEG-less seizure detection
2. Assembly of required sensors and preparation of a clinical trial
3. Clinical trial
We recommend to perform part 1 & 2 prior to the “Freisemester”.
Automatic (computer-based) prediction of epileptic seizures can bring great benefits to the patients. There is currently a lot of research going on the topic, where primary EEG, but also e.g. EMG data has been used. We propose a retrospective study of video EEG data collected in Epileptology UKA. The task of the MD student is to extract the relevant data from the records and in collaboration with a data analyst try to identify individual patterns which might be used for seizure detection.