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