A complete EEG Motor Imagery Classification pipeline
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BCI's measure brain activity, process it, and produce control signals that reflect the user's intent. We aim to detect and classify patterns of activity in the ongoing brain signals that are associated with specific tasks or events.
A common mental strategy is called motor imagery. In our implementation, we aim to tell if the users are thinking of moving your left hand, right hand, or not moving (idle).
To get a local copy up and running follow these simple example steps.
- Install python modules
pip install bci4als
For more examples, please refer to the examples
Please see the developer's guide
See the open issues for a list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Evyatar Luvaton - luvaton@post.bgu.ac.il
Noam Siegel - noamsi@post.bgu.ac.il
Adi Nissim - adinis@post.bgu.ac.il
Eden Zohar - edenzo@post.bgu.ac.il
Project Link: https://github.com/evyatarluv/BCI-4-ALS