Abstract
A computational framework to support seizure predictions in epileptic patients is presented. It is based on mining and knowledge discovery in Electroencephalogram (EEG) signal. A set of features is extracted and classification techniques are then used to eventually derive an alarm signal predicting a coming seizure. The epileptic patient may then take steps in order to prevent accidents and social exposure.
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Direito, B., Dourado, A., Sales, F., Vieira, M. (2008). An Application for Electroencephalogram Mining for Epileptic Seizure Prediction. In: Perner, P. (eds) Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects. ICDM 2008. Lecture Notes in Computer Science(), vol 5077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70720-2_7
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DOI: https://doi.org/10.1007/978-3-540-70720-2_7
Publisher Name: Springer, Berlin, Heidelberg
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