Zongxin Xu
Papers
1
Total Citations
24
H-Index
1
About
Zongxin Xu is a leading researcher in brain-computer interfaces (BCI) and neural signal processing, with a particular focus on motor imagery-based systems for neurorehabilitation and robotic control. His most cited work, "Recognition of single upper limb motor imagery tasks from EEG using multi-branch fusion convolutional neural network" (2023, 24 citations), addresses a critical gap in the field by developing advanced deep learning methods to decode complex, single-limb motor intentions from EEG signals. This innovation significantly expands the practical applicability of MI-BCI, moving beyond traditional bilateral tasks to enable more natural and precise control for assistive technologies. Xu’s contributions are pivotal for advancing neurorehabilitation therapies and intuitive human-robot interaction, demonstrating clear translational impact. His work is widely recognized for its technical rigor and clinical relevance, establishing him as a key figure in the next generation of BCI research.
Research Focus
Key Achievements
Top Papers
- 1