SCU

Code to accompany our 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) paper entitled - On the classification of SSVEP-based dry-EEG signals via convolutional neural networks.

Usage

A working example demonstrating how to train a model can be found in the Simple_train.py file, which can be directly run with the included sample data in this repo. The base SCU model is included in the SCU.py file, and can be used to directly import the model into other codebases.

Dependencies and Requirements

The code has been designed to support python 3.6+ only. The project has the following dependencies and version requirements:

• torch=1.1.0+
• numpy=1.16++
• python=3.6.5+
• scipy=1.1.0+
• scikit-learn=0.23+

Cite

Please cite the associated papers for this work if you use this code:

@inproceedings{aznan2018classification,
  title={On the classification of SSVEP-based dry-EEG signals via convolutional neural networks},
  author={Aznan, Nik Khadijah Nik and Bonner, Stephen and Connolly, Jason and Al Moubayed, Noura and Breckon, Toby},
  booktitle={2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
  pages={3726--3731},
  year={2018},
  organization={IEEE}
}