Lan Wang
Papers
1
Total Citations
2
H-Index
1
About
Lan Wang is an emerging researcher in the field of brain-computer interface (BMI) technology, with a focused emphasis on EEG-based action recognition and its applications in rehabilitation engineering. Her work centers on developing classification frameworks for motor intention decoding from electroencephalographic signals, contributing to the growing body of knowledge that bridges neuroscience and assistive robotics. Her most notable publication, "Research on two-class and four-class action recognition based on EEG signals" (2023), addresses the critical challenge of accurately distinguishing motor commands for use in lower limb rehabilitation robots and human exoskeletons — technologies that hold transformative potential for patients with motor disorders. This work reflects a broader commitment to improving the quality of life for individuals with physical disabilities through intelligent, brain-driven control systems. Although early in her citation trajectory with 2 citations, Wang's research aligns with one of the most rapidly expanding areas of biomedical engineering, where demand for robust, real-time neural decoding solutions continues to accelerate. Her contributions represent a promising foundation for future advances in neuroprosthetics and human-machine interaction research.
Research Focus
Key Achievements
Top Papers
- 1