Papers

16

Total Citations

414

H-Index

10

About

Huijun Li is a prominent robotics and rehabilitation engineering researcher whose work sits at the intersection of intelligent control systems, human-robot interaction, and stroke recovery technology. Over more than a decade, Li has made substantial contributions to the design and control of upper-limb rehabilitation robots, pioneering adaptive control strategies that respond dynamically to individual patient needs. His early landmark papers from 2010, which together have garnered over 160 citations, established foundational control frameworks using the Barrett WAM Arm platform and introduced evolutionary dynamic recurrent fuzzy neural networks for adaptive impedance control — enabling robots to respond intelligently to the changing biomechanical states of stroke patients. Li further advanced the field through impedance identification techniques, backstepping adaptive control, and hierarchical safety supervisory systems that protect patients during unexpected events like spasms. His 2021 cable-driven wrist exoskeleton demonstrated innovative workspace expansion using distributed actuation, while his telerehabilitation system enabling one therapist to simultaneously treat three remote patients reflects a forward-thinking approach to scalable clinical care. With nearly 400 cumulative citations across his most influential works, Li's research continues shaping the future of accessible, intelligent robotic rehabilitation.

Research Focus

Key Achievements

10
H-Index
16
Papers
414
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive Impedance Control for Upper-Limb Rehabilitation Robot Using Evolutionary Dynamic Recurrent Fuzzy Neural Network
84 citations · 2010
📈 Most Prolific Year: 2010 (3 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Southeast University, State Key Laboratory of Digital Medical Engineering

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago