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bci4als 0.36.1

BCI - 4 - ALS

A complete EEG Motor Imagery Classification pipeline

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Table of Contents

About The Project

Built With

Getting Started

Prerequisites
Installation

Usage
Roadmap
Contributing
License
Contact
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

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.

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

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

Contact
Evyatar Luvaton - luvaton@post.bgu.ac.il
Noam Siegel - noamsi@post.bgu.ac.il
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