Mengjun Zhang

Nanjing University of Science and Technology

Papers

Total Citations

H-Index

About

Dr. Mengjun Zhang is a leading researcher at the intersection of assistive robotics, rehabilitation engineering, and human–machine interaction. Her primary focus lies in developing intelligent, wearable robotic systems that restore hand function for individuals with neurological impairments, such as stroke survivors. Dr. Zhang’s most cited work, “Toward Hand Pattern Recognition in Assistive and Rehabilitation Robotics Using EMG and Kinematics” (2021, 32 citations), represents a pivotal contribution to the field. In this study, she pioneered a hybrid pattern recognition framework that fuses electromyography (EMG) signals with kinematic data, significantly improving the accuracy and responsiveness of hand exoskeletons. This approach is critical for enabling intuitive, real-time control of assistive devices, moving beyond simple binary commands to nuanced, multi-gesture recognition. Her research directly addresses a key bottleneck in wearable robotics: the reliable decoding of user intent. By advancing pattern recognition methodologies, Dr. Zhang’s work lays the groundwork for more natural and effective rehabilitation therapies, promising to enhance the quality of life for patients recovering from stroke or living with motor disabilities. Her contributions are shaping the next generation of smart, adaptive hand robots.