bci4als 0.36.1

A complete EEG Motor Imagery Classification pipeline

BCI - 4 - ALS

A complete EEG Motor Imagery Classification pipeline
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Roadmap
5. Contributing
6. License
7. Contact
8. Acknowledgements

About The Project

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).

Built With

• psychopy
• MNE-features
• Keras
• scikit-learn

Getting Started

To get a local copy up and running follow these simple example steps.

Prerequisites

• LabRecorder
• OpenBCI GUI (recommended)

Installation

1. Install python modules

   pip install -i https://test.pypi.org/simple/ bci4als
   

Usage

For more examples, please refer to the [examples][examples-url]

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

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.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Evyatar Luvaton - [e-mail]

Noam Siegel - [e-mail]

Project Link: https://github.com/evyatarluv/BCI-4-ALS

Acknowledgements

• Computational Psychiatry Lab @ BGU
• Lab Streaming Layer
• MIT License

[examples-url]: recycle bin/semester A report/Report.ipynb