Yanyan Chang
Papers
2
Total Citations
7
H-Index
2
About
Yanyan Chang is a researcher in the field of medical robotics, with a focused expertise in upper limb rehabilitation robot design and control. Her work addresses the critical challenge of ensuring safe, compliant human-robot interaction for patients undergoing physical therapy. Chang’s major contributions include developing kinematics analysis and trajectory planning methods for three-degree-of-freedom upper limb rehabilitation robots, as detailed in her most-cited 2017 paper (5 citations). She further advanced the field by proposing an impedance control strategy integrated with neural networks (2 citations, 2017), which enables the robot to adapt its stiffness in real-time based on patient-applied forces, enhancing both safety and therapeutic effectiveness. This neural-network-based approach represents a notable achievement in creating more robust and responsive control systems for direct patient-contact robots. While her citation counts reflect a developing career, her work is foundational for researchers exploring compliant control in rehabilitation robotics. Chang’s research is particularly valuable for students and engineers seeking to understand the intersection of robotics, control theory, and neural networks in medical applications, offering practical solutions for improving patient outcomes through intelligent robotic assistance.
Research Focus
Key Achievements
Top Papers
- 1
- 2