基于动态视觉范式与实时反馈校验的脑控机械臂

A dynamic brain control vision paradigm and a real-time feedback brain command verification method applied to the brain control robot arm are proposed, and a set of brain control robotic arm system is realized based on the proposed paradigm and method. Compared with the fixed stimulus position and sequential control paradigm of brain computer interfaces, the paradigm outputs object-oriented brain control commands based on the dynamic stimulus, and fast capture based on brain-machine cooperation is realized. On the other hand, in view of the low accuracy of brain feature recognition and insufficient robustness of the system in the process-oriented brain computer interface, this research proposes a real-time feedback verification method. Based on this method, the raw brain command can be verified via dynamic frequency adjustment, which can effectively improve the accuracy of the brain controlled robot arm in brain command recognition. Result shows the dynamic stimulation and real-time feedback verification method has an average success rate of 85% (47.9% for the control method based on motion process) for brain controlled grasping, and an average time consumption of 22.46 s (64.76 s for the control method based on motion process) for a single grasping task. In the future, the framework of the brain controlled robot arm proposed can be integrated into the robot operating system in the form of node modules, and applied to the closed-loop control of the brain-machine cooperative systems.