Welcome to the BrainBoard project repository. This project is a comprehensive Brain-Computer Interface (BCI) system developed by KN Neuron (Neuroinformatics Student Research Group, Wrocław University of Technology).
BrainBoard leverages EEG signals—specifically motor imagery (MI)—to drive a variety of applications, from experimental setups to a functional BCI keyboard.
It was developed by:
This repository serves as a central hub for the following components, included as submodules:
A modular Python pipeline for classifying motor imagery (left-hand, right-hand, and rest).
- Dataset: PhysioNet EEG Motor Movement/Imagery Dataset.
- Pipeline: Includes data downloading, preprocessing, training loops, and cross-validation.
- Goal: To provide robust models for MI classification.
A Pygame-based experimental environment that integrates GUI, EEG headset, and data management.
- GUI: Immersive interface for users during BCI experiments.
- Integration: Seamlessly connects with EEG headsets for real-time data acquisition.
- Hex-O-Spell: Includes components for the Hex-O-Spell speller paradigm.
A functional motor-imagery BCI keyboard.
- Input Signals: Left-hand MI, right-hand MI, and deliberate eye blinks.
- Architecture: Features a BCI pipeline (EEGNet for MI, blink detection, smoothing/debounce) driving a sector/letter speller state machine.
- Hardware Support: Compatible with BrainAccess, BioAmp EXG, and MIDI/Mock playback.
To clone this repository along with all its submodules, use:
git clone --recursive https://github.com/KN-Neuron/Brainboard.gitIf you have already cloned the repository, you can initialize and update the submodules with:
git submodule update --init --recursiveKN Neuron is a student research group at Wrocław University of Technology focused on neuroinformatics, brain-computer interfaces, and signal processing.
This project is licensed under the terms of the LICENSE file found in the root directory.