Mindset—A General Purpose Brain–Computer Interface System for End-Users

Abstract

Existing brain-computer interface (BCI) software platforms are typically designed for research purposes and offer limited usability for non-technical end-users. This paper presents the Mindset software application, which allows end-users to train and use a BCI through a graphical user interface. The four modules of Mindset (acquisition, visualization, training, and output) collectively provide functionality to connect to various EEG hardware, visualize incoming data streams, perform user training for mental imagery and visual P300 paradigms, and facilitate real-time control of a diverse range of applications. Online experiments were conducted to characterize system performance during motor imagery and visual P300 tasks with different EEG headsets and computing hardware. With both motor imagery and visual P300 paradigms, and two different headsets and two different computer configurations, output latency was no greater than 30 ms, latency jitter below 10 ms and system clock jitter less than 17 ms. Further, the prototypical event-related potential morphology was confirmed in the visual P300 paradigm, while the expected contralateral desynchronization was observed in the motor imagery paradigm. These results demonstrate that Mindset can satisfy the real-time requirements of a BCI system and reliably capture relevant neurophysiological signals with readily available computing hardware. Mindset facilitates the translation of BCI research into clinical and practical use by improving the accessibility and usability of BCI technology.

Keywords

• Brain-computer interface (BCI)
• electroencephalography (EEG)
• software design