EasyBCI: Cross-platform General Purpose EEG Interface for Game and Application Inputs

[Dooganar]

Title

EasyBCI: Cross-platform General Purpose EEG Interface for Game and Application Inputs

Short description and the goals for the OHBM BrainHack

This project develops a customization interface that translates EEG signals into computer inputs. Users can train the system to recognise distinct brainwave patterns (mental/motor imagery), each of which corresponds to a configurable metric/class. These metrics are then dynamically mapped to specific computer keys (or mouse input), enabling EEG-based interaction with games, applications, or custom software environments.

Behind the scenes is the EEGNet classifier. Find out more about the classifier here. The aim is that this application will train the model locally on the users machine, and use it to predict the class of the EEG data, and then map it to the a computer input (keyboard or mouse). The user can then theoretically use their EEG to control any program on their computer, and have full control over the interface. We currently support the Neurosity Crown and the OpenBCI Cyton devices, but this can be easily expanded to more. This project is committed to free and open source practices for it's entire lifecycle.

Link to the Project

https://github.com/Dooganar/bioe6100-MI-EEG-classification

Image/Logo for the OHBM brainhack website

https://raw.githubusercontent.com/Dooganar/bioe6100-MI-EEG-classification/refs/heads/main/images/EasyBCI-logoA.png

Project lead

Reuben Richardson
Github username: "Dooganar"
Discord username: "dooganar"

Main Hub

Brisbane

Link to the Project pitch

No response

Other hubs covered by the leaders

• Brisbane
• Hybrid (Asia / Pacific)
• Hybrid (Europe / Middle East / Africa)
• Hybrid (Americas)

Skills

• Signal Processing – Understanding of EEG signals
• Machine Learning (ML) – Basic ML for pattern recognition and classification of EEG inputs.
• Software Development – Experience with Python or similar for building the interface and training modules.

Recommended tutorials for new contributors

https://neuro.inf.unibe.ch/AlgorithmsNeuroscience/Tutorial_files/DataLoading.html

Good first issues

No response

Twitter summary

No response

Short name for the Discord chat channel (~15 chars)

EasyBCI

Please read and follow the OHBM Code of Conduct

• I agree to follow the OHBM Code of Conduct during the hackathon

[bhvieira]

If you haven't done so already, please share a brief project pitch slide deck with us at ohbmopenscience@gmail.com (~4 minutes, depending on the number of projects). Google Slides is the most convenient format for us.
If you have done it already, please disregard this message. Thank you! 🙂