EEGUnity

<img src="./docs/source/_static/logo.png" alt="Project Logo" width="20%">

Overview

EEGUnity is a Python package designed for processing and analyzing large-scale EEG data efficiently. This guide will walk you through the Usage on Windows, macOS, and Linux. For more details on the motivation, concepts, and vision behind this project, please refer to the paper EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model

Project Documentation

You can view the API Reference and Tutorial through the following link: Click here to view the manual

Usage in Python Project

1. Create a Python Environment

"Ensure you are using Python version 3.6 or higher. Due to compatibility issues with the latest version of NumPy, Python 3.13 is currently not supported.

2. Install EEGUnity via pip

Run the following command to install EEGUnity:

pip install eegunity

3. Import EEGUnity in Your Python Project

Use the following import statement to include the package:

from eegunity import UnifiedDataset

Tutorial

1. How does EEGUnity support multi-modal data: Click here to view the tutorial
2. How to Format Channel Name and Inspect MetaData: Click here to view the tutorial
3. How to Make Standard Datasets: Click here to view the tutorial
4. How to Process Data and Export as h5Dataset: Click here to view the tutorial
5. How to Process Data Using Multiple Computers with EEGUnity: Click here to view the tutorial
6. How to Read h5Dataset: Click here to view the tutorial
7. How to Speep Up with Multithread: Click here to view the tutorial
8. How to Reading Rich Meta Data via Kernel: Click here to view the tutorial