Papers
14
Total Citations
204
H-Index
7
About
Lincong Luo is a robotics and rehabilitation engineering researcher whose work sits at the intersection of human-robot interaction, motor control, and assistive technology. Specializing in upper-limb rehabilitation robotics, Luo has made significant contributions to the design, control, and clinical application of exoskeleton and robotic systems aimed at restoring arm function following neurological injury, particularly stroke. Among his most influential contributions is the development of an Assist-As-Needed (AAN) control framework, which has garnered over 81 citations and represents a landmark effort to promote patients' voluntary effort during robotic therapy — a critical factor in optimizing neurological recovery. His broader body of work spans adaptive impedance control, sEMG-based motion intention detection, kinematic redundancy resolution for exoskeleton trajectory planning, and CPG-inspired controllers, collectively accumulating nearly 185 citations across ten key publications. Luo has also contributed to the foundational hardware side of the field, with peer-reviewed work on multi-DOF rehabilitation robot prototypes and clinical evaluation studies. His research on physical human-robot interaction and minimum-jerk motion principles further enriches the theoretical underpinnings of safe, intuitive robotic assistance — making his work an essential reference for engineers and clinicians advancing next-generation rehabilitation technology.
Research Focus
Key Achievements
Top Papers
- 1A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation81 citations · 2019
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- 4Physical Interaction Methods for Rehabilitation and Assistive Robots13 citations · 2018
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- 7Design and control of a 3-DOF rehabilitation robot for forearm and wrist8 citations · 2017
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