Motor Imagry

Introduction

A motor Imagry task based on EEGNET and EEGTCNET.

Environment

• Ubuntu 22.04.5 LTS
• GPU NVIDIA GeForce RTX 4060
• CUDA 11.3.1
• cudnn 8.2.1.32
• python 3.7
• TensorFlow 2.7
• matplotlib 3.5
• NumPy 1.20
• scikit-learn 1.0
• SciPy 1.7

Dataset

The dataset is BCI VI-4a http://bnci-horizon-2020.eu/database/data-sets.

Reference

If you find this work useful in your research, please use the following BibTeX entry for citation.

@article{lawhern2018eegnet,
  title={EEGNet: a compact convolutional neural network for EEG-based brain--computer interfaces},
  author={Lawhern, Vernon J and Solon, Amelia J and Waytowich, Nicholas R and Gordon, Stephen M and Hung, Chou P and Lance, Brent J},
  journal={Journal of neural engineering},
  volume={15},
  number={5},
  pages={056013},
  year={2018},
  publisher={iOP Publishing}
}

@inproceedings{ingolfsson2020eeg,
  title={EEG-TCNet: An accurate temporal convolutional network for embedded motor-imagery brain--machine interfaces},
  author={Ingolfsson, Thorir Mar and Hersche, Michael and Wang, Xiaying and Kobayashi, Nobuaki and Cavigelli, Lukas and Benini, Luca},
  booktitle={2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
  pages={2958--2965},
  year={2020},
  organization={IEEE}
}