A package for modularly implenting Brain-Computer Interfaces
Project description
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 currentbuffer
of 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.
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
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