Dr. Xinjun Sheng
Project Description and Objectives
This project proposes to investigate the technology of decoding the motor unit action potential train (MUAPt) from high-density surface electromyography (EMG). This technique will be applied to an advanced dexterous human-machine interface and the corresponding system integration. High-density EMG signals and intramuscular EMG signals will be recorded concurrently to verify the decomposition algorithm and to extract spatial information of MAUPts. The relationship between hand movements and MUAPt will be analyzed to build a new control model which can realize simultaneous and proportional estimations of multiple degrees-of-freedom (DOF) kinematics. The recording channel configuration of the high-density surface, EMG, including electrode number and spatial distribution, will be optimized to improve the decomposition performance of MUAPt. This project will not only realize the simultaneous and continuous control of prosthetic hand wrist and fingers, but also provide enabling techniques for human-machine interface and dexterous prosthetics
with high transmission rate.
Interested students should have basic knowledge of robotics and signal processing.
Finish a research report.
Give two research presentations (a. references review; b. technical presentation).
Submit one paper to a journal as a co-author.