Papers
4
Total Citations
157
H-Index
4
About
Mien-Ka Duong is a leading researcher in the field of robotic exoskeletons, specializing in the critical challenge of human-robot interaction and control. His work focuses on developing intelligent control strategies that allow powered lower-limb exoskeletons to seamlessly assist human movement. Duong’s major contributions lie in the application of fuzzy logic and adaptive learning algorithms to manage the complex, dynamic forces between a human and an exoskeleton. His most cited work, “Evaluation of a Fuzzy-Based Impedance Control Strategy on a Powered Lower Exoskeleton” (47 citations), demonstrates a novel approach to regulating the stiffness and damping of the exoskeleton in real-time. Further advancing this concept, his paper “Minimizing Human-Exoskeleton Interaction Force Using Compensation for Dynamic Uncertainty Error with Adaptive RBF Network” (39 citations) introduces a sophisticated method to reduce unwanted interaction forces, making the device feel more intuitive and less burdensome. By tackling the fundamental problem of how a machine should physically respond to a human user, Duong’s research has laid essential groundwork for the next generation of assistive and rehabilitative exoskeletons, directly impacting the design of safer and more effective wearable robotics.
Research Focus
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