Driving a Semiautonomous Mobile Robotic Car Controlled by an SSVEP-Based BCI

Abstract EN

Brain-computer interfaces represent a range of acknowledged technologies that translate brain activity into computer commands.

The aim of our research is to develop and evaluate a BCI control application for certain assistive technologies that can be used for remote telepresence or remote driving.

The communication channel to the target device is based on the steady-state visual evoked potentials.

In order to test the control application, a mobile robotic car (MRC) was introduced and a four-class BCI graphical user interface (with live video feedback and stimulation boxes on the same screen) for piloting the MRC was designed.

For the purpose of evaluating a potential real-life scenario for such assistive technology, we present a study where 61 subjects steered the MRC through a predetermined route.

All 61 subjects were able to control the MRC and finish the experiment (mean time 207.08 s, SD 50.25) with a mean (SD) accuracy and ITR of 93.03% (5.73) and 14.07 bits/min (4.44), respectively.

The results show that our proposed SSVEP-based BCI control application is suitable for mobile robots with a shared-control approach.

We also did not observe any negative influence of the simultaneous live video feedback and SSVEP stimulation on the performance of the BCI system.