Design and performance study of a BMI-based hand-assisted robot

Forty-six percent of stroke patients, of whom 80 percent are not treated in a timely manner, have hand paralysis syndrome that lasts a lifetime. The integration and control of external rehabilitation devices based on EEG signal collection is gaining more attention and research, and this type of research has a wide range of directions to improve the quality of life for users. The research aims to study the design and performance of BMI-based hand-assisted robots. Existing robotics and equipment are relatively expensive, and the programmed procedures are not well adapted to different stroke users. Through experimental development and research of innovative BMI brain-computer interface devices, customized programming of experimental protocols, situational awareness of assistive robotics system data processing, brain-computer driven device testing and human-computer interaction methods, and finally after 510 practical tests concluded that patients can get significant rehabilitation process, especially for in the clinical state. The innovative system-on-a-chip research and ergonomic design confirmed that it meets the standards of rehabilitation practice and can significantly improve the patient's cognitive abilities during learning and rehabilitation and more efficiently facilitate the patient's recovery.