Our Ph.D. candidate Yichuan Jiang proposed a uniﬁed EEG-fNIRS bimodal signal processing framework to characterize neural activities-induced by robot-assisted bimanual training in IEEE Transactions on Neural Systems and Rehabilitation Engineering (IF = 3.802).
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 Nonlinear Analysis of Electroencephalogram Variability as a Measure of the Depth of Anesthesia was Reported by IEEE TIM
Our postdoc Yi-Feng Chen proposed EEG variability analysis and nonlinear models for measuring the depth of anesthesia in IEEE Transactions on Instrumentation and Measurement (IF = 4.016).