Papers
6
Total Citations
72
H-Index
4
About
Baolei Xu is a pioneering researcher in brain-computer interfaces (BCI) and brain-controlled robot interfaces (BCRI), with a focus on decoding motor imagery for direct neural control of robotic systems. His work centers on understanding how imagined movement parameters—such as force, speed, and limb selection—modulate brain activity, and on developing classification algorithms to translate these signals into commands. A standout contribution is his 2016 study (44 citations), which combined NIRS with EEG to achieve six-class classification of imagined hand clenching force and speed, demonstrating the feasibility of multi-parameter motor decoding. Earlier, Xu explored event-related potentials and spectral perturbations during fast and slow motor imagery (4 Hz vs. 1–2 Hz), showing that speed parameters can be distinguished from EEG alone. His 2012 review on direct brain-controlled robot interfaces synthesizes advances in adaptive signal classification and human-robot fusion. With over 70 combined citations, Xu’s work has advanced non-invasive BCI for real-world robotic control, offering a path toward more intuitive, speed- and force-aware neural prosthetics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Direct Brain-controlled Robot Interface Technology4 citations · 2012
- 5
- 6