Neureka-2020-Epilepsy-Challenge && Continental generalization of an AI system for clinical seizure recognition

The code implemented for 2020 Neureka-Epilepsy-Challenge paper and Continental generalization of an AI system for clinical seizure recognition.

Seizure Event Detection using minimum electrodes.

Paper version 1 release here

Please cite: https://www.sciencedirect.com/science/article/abs/pii/S0957417422012817

"Continental generalization of an AI system for clinical seizure recognition"

Preprocessing

Load raw eeg data using STFT

cd utils/
python load_data_elec_3s.py
python load_data_elec_5s.py
python load_data_elec_7s.py

Preprocessing the data with ICA

cd utils/
python ICA_load_data_elec.py

Model Training

python main.py --mode=train

Pretrained Model

Conv-LSTM pretrained model: https://drive.google.com/file/d/1Tj2JZ_B5OqZrVILg15L_lPR2DKYiBoDS/view?usp=sharing

Post Processing

Get raw results

python main.py --mode=test

Get results based on threhold and apply average method.

python main.py --mode=vote

Vote and discard short prediction

cd post_process_code/
python overlap.py 
python discard.py 
python clean.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Better contact original contributor.

Please make sure to update tests as appropriate.

License

MIT