Tianwei Zheng

Xi'an University of Science and Technology

Papers

Total Citations

H-Index

About

Tianwei Zheng is a researcher at the forefront of brain-computer interface (BCI) technology, with a focused application on assistive robotics. His work centers on decoding neural signals—particularly motor imagery EEG—to enable direct, non-muscular control of external devices, a field critical for restoring independence to individuals with severe motor impairments. Zheng’s major contributions include developing a novel “coloring and timing” BCI paradigm for nursing bed robots, which enhances user intent detection through visual and temporal cues, and pioneering a method for controlling NAO robots via imagined limb movements. These studies, each garnering around 10 citations, demonstrate practical pathways for integrating BCI with robotic systems to improve patient care. His research directly addresses the challenge of bypassing damaged neural pathways, offering a tangible bridge between human thought and machine action. By advancing both the theoretical frameworks and real-world implementations of BCI-driven robotics, Zheng is helping to shape a future where assistive technologies respond seamlessly to the user’s cognitive commands, promising greater autonomy and quality of life for those with neurological conditions.