EPILEPSIAE - A European epilepsy database



With a worldwide prevalence of about 1%, epilepsy is one of the most common serious brain diseases with profound physical, psychological and, social consequences. Characteristic symptoms are seizures caused by abnormally synchronized neuronal activity that can lead to temporary impairments of motor functions, perception, speech, memory or, consciousness.
The possibility to predict the occurrence of epileptic seizures by monitoring the electroencephalographic activity (EEG) is considered one of the most promising options to establish new therapeutic strategies for the considerable fraction of patients with currently insufficiently controlled seizures.
Here, a database is presented which is part of an EU-funded project 'EPILEPSIAE' aiming at the development of seizure prediction algorithms which can monitor the EEG for seizure precursors. High-quality, long-term continuous EEG data, enriched with clinical metadata, which so far have not been available, are managed in this database as a joint effort of epilepsy centers in Portugal (Coimbra), France (Paris) and Germany (Freiburg).
The architecture and the underlying schema are here reported for this database. It was designed for an efficient organization, access and search of the data of 300 epilepsy patients, including high quality long-term EEG recordings, obtained with scalp and intracranial electrodes, as well as derived features and supplementary clinical and imaging data. The organization of this European database will allow for accessibility by a wide spectrum of research groups and may serve as a model for similar databases planned for the future.


Database; Schema; Epilepsy; Seizure prediction; EEG


Computer methods and programs in biomedicine, January 2012

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Year 2016 : 11 citations

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 Qaraqe, M., Ismail, M. and Serpedin, E., 2016, August. Combined matching pursuit and Wigner-Ville Distribution analysis for the discrimination of ictal heart rate variability. In Signal Processing Conference (EUSIPCO), 2016 24th European (pp. 2045-2049). IEEE.

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Year 2015 : 7 citations

 Meisel, Christian, et al. "Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle." Proceedings of the National Academy of Sciences 112.47 (2015): 14694-14699.

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 Kini, Lohith G., Kathryn A. Davis, and Joost B. Wagenaar. "Data integration: Combined imaging and electrophysiology data in the cloud." NeuroImage 124 (2016): 1175-1181.

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 Behbahani, Soroor, et al. "Classification of ictal and seizure-free HRV signals with focus on lateralization of epilepsy." Technology and Health Care Preprint (2015): 1-14.

Year 2014 : 4 citations

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Year 2013 : 3 citations

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Year 2012 : 5 citations

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Year 2011 : 3 citations

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