Neurol is a python package for implementing Brain-Computer Interfaces in a modular manner. With the help of tools in this package, you will be able define the behavior of your intended BCI and easily implement it. A neurol BCI is defined by a number of components:

• A classifier which decodes brain data into some kind of 'brain-state'
• An action which provides feedback depending on the decoded 'brain-state'
• An optional calibrator which runs at startup and modifies the operation of the BCI
• An optional transformer which transforms the current buffer of data into the form expected by the classifier

The neurol BCI manages an incoming stream of brain data and uses the above user-defined functions to run a brain-computer interface.

The package includes generic utility functions to aid in creating classifier's, transfromer's, and calibrator's for common BCI use-cases. It also comes prepackaged with a growing list of trained machine learning models for common BCI classification tasks.

Installation

neurol can be easily installed using pip:

$ pip install neurol

Documentation

Please find neurol's documentation here.

You can also find example notebooks in the examples directory.

Contact

If you have questions or would like to discuss this package, please don't hesitate to contact me.

Awni Altabaa - awni.altabaa@queensu.ca / awnyaltabaa@gmail.com