Xiaolei Feng

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About

Xiaolei Feng is a leading researcher in brain–computer interfaces (BCIs) and robotic control systems, with a particular focus on steady-state visual evoked potential (SSVEP)-based technologies. Their most influential work, "Control of the robotic arm system with an SSVEP-based BCI" (2024), has already garnered 8 citations, demonstrating early impact in this rapidly evolving field. Feng’s primary contribution lies in developing precise, real-time online control methods that enable individuals with movement disorders to interact more effectively with robotic systems. By optimizing the speed and accuracy of SSVEP-based BCI commands, their research bridges critical gaps between neural signal processing and practical robotic manipulation. This work holds transformative potential for assistive technologies, offering enhanced human–computer interaction for those with severe motor impairments. Feng’s achievements are notable for advancing the feasibility of high-performance, non-invasive BCI systems in real-world applications, making them a rising figure in neuroengineering and rehabilitation robotics.