Jingyan Hu
Papers
2
Total Citations
19
H-Index
2
About
Jingyan Hu is a leading researcher in the field of rehabilitation robotics and human-robot interaction, with a focus on enhancing motor function assessment and learning. Her work centers on understanding how robotic systems can be used to evaluate and improve upper-limb motor control, particularly through the analysis of muscle synergy features during tasks like circle-drawing. Hu’s most-cited paper, “Upper-Limb Muscle Synergy Features in Human-Robot Interaction with Circle-Drawing Movements” (2021, 16 citations), introduces innovative methods for using kinematic and kinetic data from motion and force sensors to assess motor function, offering a robust tool for rehabilitation robots. She further explores the optimization of training outcomes in her 2023 study, “Effects of Error Modulation-Based Visual and Haptic Feedback Fusion Strategies on Motor Learning and Motivation” (3 citations), which investigates how combining visual and haptic feedback can enhance both skill acquisition and user engagement. Hu’s contributions are pivotal in advancing robot-assisted rehabilitation, bridging the gap between technology and patient motivation. Her work has been recognized for its potential to transform clinical practices, making her a notable figure in the intersection of robotics, neuroscience, and motor learning.
Research Focus
Key Achievements
Top Papers
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