This is project is an attempt to predict epileptic seizure onset using machine learning techniques on EEG signals.

The CHB-MIT Scalp EEG Database has been used in this project.

Features have been extracted from the dataset using mne and pyeeg

The extracted features are:

• Mean Variance
• Mean Kurtosis
• Mean Skewness
• Petrosian Fractal Dimension
• Hjorth Mobility
• Hjorth Complexity
• Mean Spectral Entropy

• SVM
• RNN
• R-LSTM