Papers
1
Total Citations
9
H-Index
1
About
Khai Dang is a researcher whose work bridges computational optimization and biomechanics, with a primary focus on solving complex inverse kinematic problems for human motion analysis. His most-cited paper, "Simulation and Experiment in Solving Inverse Kinematic for Human Upper Limb by Using Optimization Algorithm" (2021), has garnered 9 citations, demonstrating his ability to integrate simulation and experimental validation to model upper limb movement. This work contributes to fields such as rehabilitation robotics, prosthetics, and ergonomics, where precise motion tracking is critical. Dang’s research emphasizes the use of optimization algorithms to enhance accuracy and efficiency in kinematic solutions, offering practical tools for engineers and clinicians. By combining theoretical modeling with real-world experimentation, he provides a robust framework for understanding human joint dynamics. His contributions are particularly valuable for students and researchers exploring the intersection of robotics, control systems, and human physiology. As his citation count grows, Dang’s work continues to influence the development of assistive technologies and motion analysis systems, marking him as an emerging voice in applied computational biomechanics.
Research Focus
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Top Papers
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