Papers
5
Total Citations
24
H-Index
3
About
Li-Jun Han is a rising researcher at the intersection of biomechanics, robotics, and human-machine interaction, with a primary focus on musculoskeletal modeling and exoskeleton control. His work addresses the critical challenge of creating personalized, physiologically accurate models for real-time motion estimation and assistive device control. Han’s major contributions include developing hierarchical optimization frameworks for personalized hand and wrist musculoskeletal modeling, achieving more accurate motion estimation from surface electromyography (sEMG) signals. He has also pioneered physics-informed deep transfer learning techniques that integrate human physiological knowledge with neural networks to simultaneously estimate multiple joint angles and torques, bridging the gap between computational efficiency and biological fidelity. His innovative neurologically inspired transparent interaction paradigm for wearable exoskeletons aims to eliminate the stiffness and lag that plague current assistive devices, enabling natural, fast movements. With his most cited work (14 citations) already demonstrating impact, Han’s research is laying the groundwork for next-generation human-robot collaboration systems, from rehabilitation exoskeletons to intuitive prosthetic control.
Research Focus
Key Achievements
Top Papers
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- 4A Compliant Elbow Exoskeleton with an SEA at Interaction Port2 citations · 2023
- 5Learning Stable Nonlinear Dynamical System from One Demonstration2 citations · 2023