EEGDojo🥋

Your Personal EEG Processing Toolkit

Welcome to EEGDojo, a powerful and versatile toolbox for EEG signal preprocessing and artifact detection. Whether you're a beginner or an expert in EEG analysis, EEGDojo provides clean, structured, and efficient workflows to detect bad channels, run ICA, and clean EEG data like a pro.

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Features 🧠

• Modular and Customizable: Run modular bad channel detection methods (e.g., Kurtosis, Spectrum, ICLabel).
• ICA Automation: Integrates ICLabel, FASTER, and spatial filtering methods.
• User-Friendly: Output reports and logs for transparency and reproducibility.
• Visualization-Ready: Automatically saves bad channel/component properties for review.
• Flexible Integration: Suitable for EEGLAB pipelines and EEG research workflows.

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Table of Contents

1. Installation
2. Usage
3. Example Workflow
4. Contributing
5. License

Installation ⚙️

Clone the repository:

git clone https://github.com/yourusername/EEGDojo.git

Usage 🚀

Example pipeline for bad channel detection and ICA artifact removal:

% Load EEG data
EEG = pop_loadset('filename', 'example_data.set');

% Set parameters
params = load('params_example.mat');

% Run bad channel detection
[EEG, BadChan] = detect_badchannels(EEG, params);

% Run ICA and remove bad components
[EEG, BadICs] = EEGdojo_remove_badICs(EEG, params, 1);

% Save cleaned data
pop_saveset(EEG, 'filename', 'example_data_cleaned.set');

Example Workflow 📊

Below is a sample workflow for EEG data preprocessing:

Detect bad channels using modular methods (e.g., Spectrum, Kurtosis, CleanRawData). Run ICA to identify and remove bad components. Save results and export logs/visualizations for further analysis.

Contributing 🤝

We welcome contributions to EEGDojo! Whether it's fixing a bug, adding new features, or improving documentation, feel free to fork this repository and submit a pull request.

License 📄

This project is licensed under the MIT License.

Enjoy EEG processing like a ninja in the EEG dojo! 🥋