In this project, I experimented with Bonn University's Epilepsy EEG signals dataset. As shown above, different notebooks mainly revolve around the preprocessing, feature extraction, feature selection, and modelling phases. Using Machine Learning algorithms such as KNN, SVM, LDA, and Neural Networks, an accuracy of 98% has been successfully obtained in classifying epileptic and non-epileptic EEG signals.
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Ledengary/Epilepsy-EEG-Signal-Processing
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Classifying epileptic and non-epileptic EEG signals using Machine and Deep Learning.
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