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bci-hil

The brain computer interface human-in-the-loop research framework

This page contains the supplementary material for the Frontiers in Neuroscience method paper

"An Open-Source Human-in-the-Loop BCI Research Framework: Method and Design"

by Martin Gemborn Nilsson, Pex Tufvesson, Frida Heskebeck, and Mikael Johansson.

Department of Automatic Control, Lund University, Lund, Sweden.

ABSTRACT: Brain-computer interfaces (BCIs) translate brain activity into digital commands for interaction with the physical world. The technology has great potential in several applied areas, ranging from medical applications to entertainment industry, and creates entirely new conditions for basic research in cognitive neuroscience. The BCIs of today, however, offer only crude online classification of the user’s current state of mind, and more sophisticated decoding of mental states depends on time-consuming offline data analysis. The present paper addresses this limitation directly by leveraging a set of improvements to the analytical pipeline to pave the way for the next generation of online BCIs. Specifically, we present an open-source framework with a modular and customizable hardware-independent design, comprising a human-in-the-loop (HIL) model training and retraining, real-time stimulus control in a BCI-HIL research framework, enabling transfer learning and cloud computing for online classification of electroencephalography (EEG) data. Stimuli for the subject and diagnostics for the researcher are shown on separate displays using web browser technologies. Messages are sent using the Lab Streaming Layer standard and websockets. Real-time signal processing and classification, as well as training of machine learning models, is facilitated by the open-source Python package Timeflux. The framework runs on Linux, MacOS, and Windows. While online analysis is the main target of the BCI-HIL framework, offline analysis of the EEG data can be performed with Python, MATLAB, and Julia through packages like MNE, EEGLAB, or FieldTrip. The paper describes and discusses desirable properties of a human-in-the-loop BCI research platform. The BCI-HIL framework is released under MIT license.

The published paper can be found here: www.frontiersin.org/articles/10.3389/fnhum.2023.1129362/full 

Checkout the supplementary material, source code and documentation from GitHub:
github.com/bci-hil/bci-hil

Questions? martin [dot] gemborn_nilsson [at] control [dot] lth [dot] se

29 Sep 2023