Affiliation:
1. School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200000, China
2. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China
Abstract
To address the rehabilitation needs of upper limb hemiplegic patients in various stages of recovery, streamline the workload of rehabilitation professionals, and provide data visualization, our research team designed a six-degree-of-freedom upper limb exoskeleton rehabilitation robot inspired by the human upper limb’s structure. We also developed an eight-channel synchronized signal acquisition system for capturing surface electromyography (sEMG) signals and elbow joint angle data. Utilizing Solidworks, we modeled the robot with a focus on modularity, and conducted structural and kinematic analyses. To predict the elbow joint angles, we employed a back propagation neural network (BPNN). We introduced three training modes: a PID control, bilateral control, and active control, each tailored to different phases of the rehabilitation process. Our experimental results demonstrated a strong linear regression relationship between the predicted reference values and the actual elbow joint angles, with an R-squared value of 94.41% and an average error of four degrees. Furthermore, these results validated the increased stability of our model and addressed issues related to the size and single-mode limitations of upper limb rehabilitation robots. This work lays the theoretical foundation for future model enhancements and further research in the field of rehabilitation.
Funder
Ministry of Science and Technology of the People’s Republic of China
Translational Medicine National Major Science and Technology Infrastructure (Shanghai) Open Subject Fund
Shanghai Jiao Tong University School of Medicine, Geogao University Double Hundred Program
Shanghai Jiao Tong University School of Medicine, Translational Medicine Innovation Fund
Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine
National Natural Science Foundation of China
Shanghai Science and Technology Commission
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry