On 27 June 2020, Prof. Guanglin Li, the researcher of the Key Laboratory of the human-computer intelligent collaborative system of the Chinese Academy of Sciences, was invited by Prof. Mingming Zhang to give an online lecture on the Tencent Meeting.
Welcome to Brain-Robot Rehabilitation Technology Lab. Our lab aims at using robots, artificial intelligence, neuroscience, and other technical methods to develop an accurate, real-time closed-loop, life task-oriented neural rehabilitation system.
Our lab is led by Prof. Mingming Zhang, who is a PI and doctoral supervisor of the Department of Biomedical Engineering, SUSTech. Now, there are 3 postdoctoral fellows, 3 doctoral students, 5 master students, and 2 research assistants in our lab.
At present, our team has carried out research in the fields of (1) physical human-robot interaction, (2) brain-computer interfaces for neural rehabilitation, and (3) wearable robotics for rehabilitation and enhancement.
Physical Human-Robot Interaction
Brain-Computer Interfaces for Neural Rehabilitation
Wearable Robotics for Rehabilitation and Enhancement
Research Progress in the Performance-based Iterative Learning Control Strategy for Task-oriented Rehabilitation was Reported by IEEE TCDS
Our postdoctoral researcher, Dr. Miao Qing proposed a performance-based iterative learning control strategy for task-oriented rehabilitation in IEEE Transactions on Cognitive and Developmental Systems (IF = 2.667). This method could be used for robot-assisted upper limb training, which can adaptively and rapidly convergent to subject-specific training difficulty levels for maximizing active participation of the patients.
Our postdoctoral researcher, Dr. Li Ping proposed an active disturbance rejection control (ADRC) method by combining 2-DOF internal model control (IMC) rules and linear extended state observer (LSO) in IEEE Transactions on Industrial Electronics (IF = 7.503). This method could be used for motion control of servo motor drive system with network communication delay, which significantly improves the control accuracy of servo system under parameter uncertainty and external disturbance.