BCI.js - An Electroencephalography Toolkit Built on Modern Web Technologies

Software environments used to create current neurotechnologies are often designed for developers experienced with languages such as Matlab, C++, Java, and Python. This research investigates the feasibility of JavaScript as a development platform for non-critical BCI systems. BCI.js is a JavaScript library that provides the basic tools necessary to run a BCI system entirely within a web browser. BCI.js builds upon existing JavaScript mathematical libraries such as Math.js and Numeric JavaScript, adding BCI-specific paradigms such as common spatial pattern (CSP), machine learning tools such as linear discriminant analysis (LDA), and signal processing methods such as power spectral density (PSD), band power extraction, and fastICA.

View Publication: Webbci: An electroencephalography toolkit built on modern web technologies

View Documentation: bci.js.org

Read Article: EEG Motor Imagery Classification in Node.js with BCI.js