Xuefei Zhao
Papers
2
Total Citations
13
H-Index
2
About
Xuefei Zhao is a rising researcher in the field of brain-computer interfaces (BCI), with a focused expertise in motor imagery (MI) electroencephalography (EEG) for robotic control. Her primary contributions lie in developing innovative coding schemes to translate neural signals into precise, multi-degree-of-freedom commands for assistive robots. Notably, her 2022 work on a "Flexible coding scheme for robotic arm control driven by motor imagery decoding" (11 citations) proposes a novel framework to enhance the spontaneity and device independence of BCI systems. This builds on her earlier 2021 study, "Control of multiple DOFs robots using motor imagery EEG combined with Huffman coding" (2 citations), which directly tackles the critical bottleneck of limited control instruction sets in MI-based BCIs. By integrating Huffman coding with EEG decoding, Zhao’s research aims to expand the vocabulary of commands available to users, particularly stroke patients, enabling more fluid and complex interactions with robotic devices. Her work represents a significant step toward practical, high-performance BCI systems for rehabilitation and daily assistance, demonstrating a clear trajectory of innovation in neural decoding and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2