Abstract
A new system developed for real-time scalp EEG-based epileptic seizure prediction is presented, based on real time classification by machine learning methods, and named Brainatic. The system enables the consideration of previously trained classifiers for real-time seizure prediction. The software facilitates the computation of 22 univariate measures (features) per electrode, and classification using support vector machines (SVM), multilayer perceptron (MLP) neural networks and radial basis functions (RBF) neural networks. Brainatic was able to operate in real-time on a dual Intel® AtomTM netbook with 2GB of RAM, and was used to perform the clinical and ambulatory tests of the EU project EPILEPSIAE.
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Teixeira, C. et al. (2014). Brainatic: A System for Real-Time Epileptic Seizure Prediction. In: Guger, C., Allison, B., Leuthardt, E. (eds) Brain-Computer Interface Research. Biosystems & Biorobotics, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54707-2_2
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DOI: https://doi.org/10.1007/978-3-642-54707-2_2
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