README.md for BCI Experiment 1/FJ (EEG Data Analysis)

Project Overview

This repository contains a BCI (Brain-Computer Interface) experiment project focusing on EEG (Electroencephalogram) data analysis. It includes datasets from the BCI Competition 2008 - Graz data set B, scripts for data preprocessing and analysis, Jupyter notebooks for model training, and utility scripts.

Repository Structure

• dataset/: EEG data files in GDF format from BCI Competition (e.g., B0101T.gdf, B0105E.gdf, etc.)
• models/: Jupyter notebooks (svm.ipynb) and HTML outputs (svm.html) for SVM model training and analysis.
• utils/: Utility scripts like get_csv_from_gdf.py for data conversion.
• docs/: Documentation including desc_2b.pdf describing the EEG dataset.
• Other directories: archived, requirements.txt, and a Python virtual environment directory venv-bci-experiment-1.

Setup Instructions

1. Clone the Repository:

   git clone <repository-url>
   cd <repository-name>
   

2. Set Up a Python Virtual Environment:

   python -m venv venv-bci-experiment-1
   source venv-bci-experiment-1/bin/activate  # On Windows: `venv-bci-experiment-1\Scripts\activate`
   

3. Install Dependencies:

   pip install -r requirements.txt
   

4. Running the Notebooks:

   jupyter notebook
   

   Navigate to models/ to access and run the Jupyter notebooks.

Usage

• Convert GDF files to CSV using utils/get_csv_from_gdf.py for preprocessing.
• Analyze EEG data and train models using the notebooks in the models/ directory.

Contributing

Feel free to contribute to this project by submitting issues or pull requests. For detailed dataset information, refer to docs/desc_2b.pdf.