A hybrid automated detection of epileptic seizures in EEG records ?
A new automated seizure detection model is proposed. Applying Weighted Permutation Entropy to classify raw and decomposed EEG signals. Simulating physiological and environmental artifacts to test the model robustness against noise. Comparison between Support Vector Machine and Artificial Neural Network classifier. Comparison with other automatics seizure detection models found in literature.
electroencephalogram (eeg) epileptic seizure detection weighted permutation entropy (wpe) support vector machine (svm)