This repository contains the code and documentation for the data science project developed as part of the course at the Polytechnic University of Madrid. The main objective of the project is to perform the classification of motor imagery EEG signals in patients with high uncertainty using a Spectral Transformer.

• project.ipynb: Jupyter Notebook file that contains the complete project explained step by step.
• utils.py: File with utility functions required for the notebook.
• models.py: Implementation of ATCNet and Spectral Transformer.

To run the project, follow these steps:

1. Install the necessary dependencies: pip install -r requirements.txt (make sure you have the required libraries).
2. Open and run the notebook.ipynb in your Jupyter environment.

• ATCNet Paper: Link to the ATCNet paper and their original code
• Spectral Transformer Paper: Link to the Spectral Transformer paper

This project uses the following datasets:

• PhysioNet EEGMMIDB: Link to the dataset
• BCI Competition IV 2a: Link to the dataset and to the documentation

For any inquiries or collaborations, feel free to reach out:

• Email: [email protected]
• Twitter: @mixnikon

Contributions are welcome! If you wish to improve this project, please open an issue or send a pull request.