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Electroencephalogram Database: Prediction of Epileptic Seizures (RRID:SCR_008032)Copy Citation Copied
URL: https://epilepsy.uni-freiburg.de/freiburg-seizure-prediction-project
Proper Citation: Electroencephalogram Database: Prediction of Epileptic Seizures (RRID:SCR_008032)
Description: Electroencephalogram (EEG) data recorded from invasive and scalp electrodes. 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. An interdisciplinary project between: * Epilepsy Center, University Hospital Freiburg * Bernstein Center for Computational Neuroscience (BCCN), Freiburg * Freiburg Center for Data Analysis and Modeling (FDM).
Synonyms: EEG Database
Resource Type: data or information resource, database
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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