Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram
Code to reproduce results reported in our paper published as:
Truong, N. D., A. D. Nguyen, L. Kuhlmann, M. R. Bonyadi, J. Yang, S. Ippolito, and O. Kavehei (2018). "Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram." Neural Networks 105, 104-111. DOI:10.1016/j.neunet.2018.04.018.
Requirements
- h5py (2.7.1)
- hickle (2.1.0)
- Keras (2.0.6)
- matplotlib (1.3.1)
- mne (0.11.0)
- pandas (0.21.0)
- scikit-learn (0.19.1)
- scipy (1.0.0)
- tensorflow-gpu (1.4.1)
How to run the code
-
Set the paths in *.json files. Copy files in folder "copy-to-CHBMIT-folder" to your CHBMIT dataset folder.
-
Run the code
python main.py --mode MODE --dataset DATASET
where:
- MODE: cv, test
- cv: leave-one-seizure-out cross-validation
- test: ~1/3 of last seizures used for test, interictal signals are split accordingly
- DATASET: FB, CHBMIT, Kaggle2014Pred