Development of a BCI based on real-time neural source localization

Abstract

Brain-Computer-Interfaces (BCIs) provide a novel way of communication by interpreting different types of brain states. This principle of reading minds makes BCIs a challenging but at the same time fascinating topic among the different disciplines of electrophysiology and biomedical-signal-processing. This work describes the development of a non-invasive BCI approach using steadystate- visual-evoked-potentials (SSVEP) as a mental strategy. SSVEP based BCIs require an external visual stimulation, which in this work is transmitted by a LCD-screen. Consequently, a visual reactive BCI is integrated as a plug-in into the open source project MNE-CPP, which provides an extensive library for brain monitoring and processing. MNE-Scan, as a standalone software from MNE-CPP, contains the necessary real-time source localization and is used as a framework for the BCI. Moreover, an expansion with a screen keyboard device shows the BCI’s practicability. The work’s result delivers a functioning SSVEP BCI approach with an average detection accuracy of 86 %. However, it is shown, that a transition from a BCI on sensor level to a BCI on source level is challenging and requires a certain pre-development, whereby a first approach of the BCI only was realized on sensor level in this work.