Brain-Computer Interface Interaction Design Based on Fuzzy Petri Nets

Abstract

Brain-computer interaction is a new type of interaction between brain-computer interface (BCI) technology and external devices. Aiming at the situation of variable environment and unclear user intention, a brain-computer interface interaction design based on fuzzy Petri net is proposed. This paper designs a brain-computer interaction method suitable for changing scenarios. The robot can gradually ask the user questions in a dialogue way according to the change of the system state in the process of movement, to continuously clarify the user intention. In addition, the fuzzy Petri net model of the brain-computer interaction system is constructed. The feasibility and rationality are verified by building the experimental platform of the brain-computer interaction system. The results show that the brain-computer interaction based on fuzzy Petri nets is suitable for environments and tasks with uncertain tasks, and can improve the efficiency of brain-controlled robots.