Welcome to the SUSTech
Brain-Robot Rehabilitation Technology Lab

Introduction

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.

Research Areas

Physical Human-Robot Interaction

Brain-Computer Interfaces for Neural Rehabilitation

Wearable Robotics for Rehabilitation and Enhancement

News

Recent Results

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.

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Research Progress in the Field of Servo Motor Drive Control Reported by IEEE TIE

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.

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