neurol
Documentation¶
Welcome! neurol
is a python package for implementing Brain-Computer Interfaces in a modular manner. With the help of tools in the 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 the 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.