Leyun Hu
Papers
2
Total Citations
74
H-Index
2
About
Leyun Hu is a pioneering researcher at the intersection of brain–computer interfaces (BCI) and human–robot collaboration. Their work focuses on developing intelligent systems that enable seamless interaction between humans and machines, with key contributions in SSVEP-based BCI recognition algorithms and active human–robot co-carrying frameworks. Hu’s most cited paper, “An MVMD-CCA Recognition Algorithm in SSVEP-Based BCI and Its Application in Robot Control” (2021, 62 citations), introduces a novel hybrid algorithm combining multivariate variational mode decomposition and canonical correlation analysis, significantly improving the accuracy and robustness of BCI-driven robot control. This work has become a foundational reference in the field. More recently, Hu’s “A Hybrid Framework Based on Bio-Signal and Built-in Force Sensor for Human-Robot Active Co-Carrying” (2024, 12 citations) breaks new ground by integrating bio-signals with force sensors to enable active, rather than passive, collaboration—a critical advancement for future smart factories. Hu’s research not only advances theoretical understanding but also demonstrates practical applications, making them a rising leader in assistive robotics and neuroengineering.
Research Focus
Key Achievements
Top Papers
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