Xuteng Lan
Papers
2
Total Citations
9
H-Index
2
About
Xuteng Lan is a researcher at the forefront of human-machine interaction and rehabilitation robotics, with a specialized focus on decoding human motion intent from surface electromyography (sEMG) signals. His work addresses a critical challenge in assistive technology: enabling intuitive, real-time control of upper limb rehabilitation robots to support active, patient-driven therapy. Lan’s major contributions include the development of a noise-tolerant zeroing neurodynamic model integrated with LSTM networks for continuous motion estimation, and a noise-suppressing neural network approach for interactive control. These innovations are vital for creating robust systems that can accurately interpret muscle signals even in noisy, real-world clinical environments. With his most-cited papers accumulating early citations (5 and 4 respectively), Lan is establishing a strong foundation for impact in the field. His research is particularly notable for its direct application in rehabilitation medicine, where it promises to empower patients with more natural and effective robotic assistance during recovery, marking him as a promising contributor to the future of intelligent, human-centered robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2