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Time Domain Power Clough-Tocher Interpolation Imaging for Motor Imagery Classification

Semester Project at the Department of Information Technology and Electrical Engineering

How to run

Make sure the packages listed in "requirements.txt" are installed.

To run training for dataset 2a of BCI Competition IV:

  • python main_preprocess_data_bci2aiv.py -p "path/to/2a of BCI Competition IV"/data/

  • python main_train_bci2aiv.py

To run training for main_train for BCI 2000 dataset:

  • python main_preprocess_data_bci2aiv.py -p "path/to/BCI 2000/data/

  • python main_train_bci2000.py

All main_*.py scripts use argparse. Get more information by running python main_*.py -h.

References

[1] Fadel, Ward & Kollod, Csaba & Wahdow, Moutz & Ibrahim, Yahya & Ulbert, István. (2020). Multi-Class Classification of Motor Imagery EEG Signals Using Image-Based Deep Recurrent Convolutional Neural Network. 1-4. 10.1109/BCI48061.2020.9061622.

[2] Bashivan, Pouya & Rish, Irina & Yeasin, M. & Codella, Noel. (2015). Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks.

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