BciPy: brain–computer interface software in Python

ABSTRACT

There are high technological and software demands associated with conducting Brain–Computer Interface (BCI) research. In order to accelerate the development and accessibility of BCIs, it is worthwhile to focus on open-source and community desired tooling. Python, a prominent computer language, has emerged as a language of choice for many research and engineering purposes. In this article, BciPy, an open-source, Python-based software for conducting BCI research is presented. It was developed with a focus on restoring communication using Event-Related Potential (ERP) spelling interfaces; however, it may be used for other non-spelling and non-ERP BCI paradigms. Major modules in this system include support for data acquisition, data queries, stimuli presentation, signal processing, signal viewing and modeling, language modeling, task building, and a simple Graphical User Interface (GUI).

KEYWORDS:

• Electroencephalography
• EEG
• Python
• BCI
• software

Acknowledgments

We utilized many learnings from our group’s original MATLAB implementation of RSVP Keyboard [24]. We thank David Smith, Shaobin Xu, Deniz Erdogmus, Steven Bedrick, Brandon Eddy, Betts Peters, Deirdre McLaughlin, Ian Jackson, and Dani Smektala for their architectural considerations, code and feedback over the course of development.

Disclosure statement

The authors whose names are listed on this manuscript have no conflicts of interest to report.

Additional information

Funding

Funding was provided by NIH grant #R01 DC009834 and the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant #90RE507).