Investigating the EEG Embedding by Visualization

This repository is the official implementation of the paper: 'Consistent and Identifiable Latent Embedding of EEG Time-domain Features using Contrastive Learning'

The following sections guide you through cloning the project, preparing the dataset, setting up the environment, and running the code.

Clone the Project

Clone the repository using the following command:

git clone https://github.com/liangfengsid/timeEegContrastive.git
cd visContrastive

Dataset Preparation

Place the SEED dataset into the ./data directory. This dataset is used for training and evaluating the models.

Environment Setup

Create a virtual environment and install the required dependencies with the following commands:

conda create -n visContrastive python=3.11 pytorch=2.0.0
conda activate visContrastive
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple

This sets up an environment with the necessary libraries and packages for the project.

Running the Code

Data Preprocessing

Execute the following command for data preprocessing, including feature extraction and dataset splitting:

python main.py preprocess config.yaml

Model Training

Train the model to obtain latent embeddings with:

python main.py train config.yaml

Visualization

Decode using the SVM model on different embeddings and perform classification tasks with:

python main.py visualize config.yaml

Refer to the configurations in config.yaml to customize the training and other processes.

Support & Contribution

Feel free to open issues or contribute to the project. Your feedback is highly appreciated.