Cun Zhang
Papers
2
Total Citations
8
H-Index
2
About
Cun Zhang is a researcher at the forefront of human-robot interaction, specializing in the development of intelligent exoskeleton systems for rehabilitation and heavy-lifting assistance. His work uniquely bridges biomechanics and robotics, with a primary focus on analyzing surface electromyography (EMG) signals to understand and enhance human-machine co-drive systems. Zhang’s major contributions lie in the non-linear analysis of muscle coordination and fatigue. He pioneered the use of Cross Recurrence Plots (CRP) and Recurrence Quantification Analysis (RQA) to evaluate muscle fatigue in dynamic, multi-muscle movements—a significant advance over traditional linear methods, which fail to capture the complex, dynamic nature of real-world exoskeleton use. His 2019 paper on constructing muscle functional networks for exoskeleton robots (5 citations) is foundational for identifying spatial patterns in muscle activation during patient-moving tasks. His 2018 work on fatigue evaluation (3 citations) provides critical metrics for designing safer, more effective assistive devices. Though early in his career, Zhang’s innovative application of non-linear dynamics to exoskeleton control positions him as a key contributor to the next generation of adaptive, human-aware robotic systems.
Research Focus
Key Achievements
Top Papers
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