Yu Pei
Papers
1
Total Citations
87
H-Index
1
About
Yu Pei is a leading researcher at the intersection of brain–computer interfaces (BCIs), robotics, and augmented reality (AR). Their most-cited work, "Adaptive asynchronous control system of robotic arm based on augmented reality-assisted brain–computer interface" (2021, 87 citations), introduces a groundbreaking approach to improving the flexibility and practicality of brain-controlled robotic arms. By integrating AR with adaptive asynchronous control, Pei addresses a critical limitation in BCI systems—poor flexibility—enabling more intuitive and responsive robotic manipulation. This work has become a cornerstone for researchers seeking to bridge neural decoding with real-world robotic applications. Beyond this flagship study, Pei’s contributions span adaptive control algorithms and human–robot interaction, with a focus on making assistive technologies more accessible and efficient. Their research not only advances the field of neuroprosthetics but also demonstrates how AR can enhance BCI performance, opening new pathways for rehabilitation and human augmentation. With a growing citation impact, Yu Pei is recognized for pushing the boundaries of how we can seamlessly merge human intent with machine action.
Research Focus
Key Achievements
Top Papers
- 1