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Resource:Electroencephalogram Database: Prediction of Epileptic Seizures

Name: Resource:Electroencephalogram Database: Prediction of Epileptic Seizures
Description: The long-term goal of the project is to develop algorithms that are able to predict epileptic seizures with high sensitivity and specificity. These prediction algorithms could be utilized in a "brain defibrillator", in analogy to cardiac defibrillator. A prediction of seizures at an early stage could trigger an intervention to suppress the upcoming seizure by for instance electrical stimulation. Alternatively, a seizure warning device could be invented that enables behavioral adjustments.

To this aim, electroencephalogram (EEG) data recorded from invasive and scalp electrodes are analyzed in an interdisciplinary project between:

  • Epilepsy Center, University Hospital Freiburg
  • Bernstein Center for Computational Neuroscience (BCCN), Freiburg
  • Freiburg Center for Data Analysis and Modeling (FDM).

The EEG database contains invasive EEG recordings of 21 patients suffering from medically intractable focal epilepsy. The data were recorded during an invasive pre-surgical epilepsy monitoring at the Epilepsy Center of the University Hospital of Freiburg, Germany. In eleven patients, the epileptic focus was located in neocortical brain structures, in eight patients in the hippocampus, and in two patients in both. In order to obtain a high signal-to-noise ratio, fewer artifacts, and to record directly from focal areas, intracranial grid-, strip-, and depth-electrodes were utilized. The EEG data were acquired using a Neurofile NT digital video EEG system with 128 channels, 256 Hz sampling rate, and a 16 bit analogue-to-digital converter. Notch or band pass filters have not been applied.
For each of the patients, there are datasets called "ictal" and "interictal", the former containing files with epileptic seizures and at least 50 min pre-ictal data. the latter containing approximately 24 hours of EEG-recordings without seizure activity. At least 24 h of continuous interictal recordings are available for 13 patients. For the remaining patients interictal invasive EEG data consisting of less than 24 h were joined together, to end up with at least 24 h per patient.

Sponsors: This resource is supported by University of Freiburg, Germany.
Other Name(s): EEG Database
Parent Organization: University of Frankfurt; Frankfurt am Main; Germany
Resource Type(s): database
Resource: Resource
URL: https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project
Id: nif-0000-10217
Related to: Resource:3DVC
Keywords: electrode, electroencephalogram (eeg), epilepsy, epileptic seizure, focal, algorithm, analysis, behavioral, brain, cardiac, computational, data, defibrillator, hippocampus, medically, modeling, neocortical, neuroscience, patient, predict, seizure, stimulation, structure, surgical, Model
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Facts about Resource:Electroencephalogram Database: Prediction of Epileptic SeizuresRDF feed
CurationStatuscurated  +
DefiningCitationhttps://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project  +
DefinitionThe long-term goal of the project is to de The long-term goal of the project is to develop algorithms that are able to predict epileptic seizures with high sensitivity and specificity. These prediction algorithms could be utilized in a "brain defibrillator", in analogy to cardiac defibrillator. A prediction of seizures at an early stage could trigger an intervention to suppress the upcoming seizure by for instance electrical stimulation. Alternatively, a seizure warning device could be invented that enables behavioral adjustments.

To this aim, electroencephalogram (EEG) data recorded from invasive and scalp electrodes are analyzed in an interdisciplinary project between:

  • Epilepsy Center, University Hospital Freiburg
  • Bernstein Center for Computational Neuroscience (BCCN), Freiburg
  • Freiburg Center for Data Analysis and Modeling (FDM).

The EEG database contains invasive EEG recordings of 21 patients suffering from medically intractable focal epilepsy. The data were recorded during an invasive pre-surgical epilepsy monitoring at the Epilepsy Center of the University Hospital of Freiburg, Germany. In eleven patients, the epileptic focus was located in neocortical brain structures, in eight patients in the hippocampus, and in two patients in both. In order to obtain a high signal-to-noise ratio, fewer artifacts, and to record directly from focal areas, intracranial grid-, strip-, and depth-electrodes were utilized. The EEG data were acquired using a Neurofile NT digital video EEG system with 128 channels, 256 Hz sampling rate, and a 16 bit analogue-to-digital converter. Notch or band pass filters have not been applied.
For each of the patients, there are datasets called "ictal" and "interictal", the former containing files with epileptic seizures and at least 50 min pre-ictal data. the latter containing approximately 24 hours of EEG-recordings without seizure activity. At least 24 h of continuous interictal recordings are available for 13 patients. For the remaining patients interictal invasive EEG data consisting of less than 24 h were joined together, to end up with at least 24 h per patient.

Sponsors: This resource is supported by University of Freiburg, Germany.
by University of Freiburg, Germany.
Has default formThis property is a special property in this wiki.Resource  +
Has roleDatabase  +
Idnif-0000-10217  +
Is part ofUniversity of Frankfurt; Frankfurt am Main; Germany  +
KeywordsElectrode  +, Electroencephalogram (eeg)  +, Epilepsy  +, Epileptic seizure  +, Focal  +, Algorithm  +, Analysis  +, Behavioral  +, Brain  +, Cardiac  +, Computational  +, Data  +, Defibrillator  +, Hippocampus  +, Medically  +, Modeling  +, Neocortical  +, Neuroscience  +, Patient  +, Predict  +, Seizure  +, Stimulation  +, Structure  +, Surgical  +, and Model  +
LabelResource:Electroencephalogram Database: Prediction of Epileptic Seizures  +
ModifiedDate1 May 2013  +
Page has default formThis property is a special property in this wiki.Resource  +
RelatedToResource:3DVC  +
SuperCategoryResource  +
SynonymEEG Database  +