Papers
3
Total Citations
24
H-Index
2
About
Guoning Li is a researcher at the forefront of rehabilitation robotics, specializing in intelligent control strategies for upper-limb recovery. Their work focuses on developing adaptive, human-centered robotic systems that enhance motor learning and patient safety. Li’s most impactful contribution is the design of a fuzzy adaptive passive control strategy for end-effector rehabilitation robots, which dynamically adjusts assistance to avoid over-supporting patients, a common issue in conventional controllers. This paper has garnered 19 citations, reflecting its significance in improving stroke rehabilitation outcomes. Additionally, Li has explored the fusion of error-modulated visual and haptic feedback to boost motor learning and motivation, and has developed a real-time interactive force estimation method that eliminates the need for external force sensors, enhancing both safety and responsiveness in human-robot interaction. These innovations demonstrate a commitment to creating more intuitive, effective, and safe rehabilitation technologies. Li’s work is essential reading for those interested in the intersection of robotics, control theory, and neurorehabilitation.
Research Focus
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Top Papers
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