Brain-Controlled Robot Based on Augmented-Reality Brain-Computer Interface

Brain-computer interface (BCI), as a new type of human-computer interaction, has a broad application prospect in improving the lives of people with disabilities, and a great potential in empowering operators with additional executive abilities. Most of the traditional vision-based BCI use a computer screen as stimulation to evoke electroencephalogram (EEG) signals, which limits the portability of brain-controlled systems. In this paper, augmented reality (AR) technology is applied to a steady-state visual evoked potential (SSVEP) based brain-computer interface, to build an AR-based BCI robot system with an auxiliary controller based on model predictive control (MPC). The performance of the system was verified by online accuracy test and robot simulation experiments. The results of the online accuracy test show that SSVEP-BCI can still maintain high performance under the augmented reality stimulation mode, with an average accuracy of 89.19%. The experimental results of the simulation experiments show that the system is able to ensure the safety of brain-controlled robot while enhancing the portability and practicability of the brain-controlled system.