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
classifierwhich decodes brain data into some kind of 'brain-state' - An
actionwhich provides feedback depending on the decoded 'brain-state' - An optional
calibratorwhich runs at startup and modifies the operation of the BCI - An optional
transformerwhich transforms the currentbufferof data into the form expected by theclassifier
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.
neurol can be easily installed using pip:
$ pip install neurol
Please find neurol's documentation here.
You can also find example notebooks in the examples directory.
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