Jialing Wang
Papers
1
Total Citations
7
H-Index
1
About
Jialing Wang is a leading researcher at the intersection of brain–computer interfaces (BCI), motor imagery (MI), and humanoid robotics. Wang’s most cited work, “Using Humanoid Robots to Obtain High-Quality Motor Imagery Electroencephalogram Data for Better Brain–Computer Interaction” (2023, 7 citations), addresses a critical bottleneck in BCI: the difficulty users face in generating high-quality EEG signals during motor imagery tasks. By introducing humanoid robots as a novel stimulation paradigm, Wang demonstrates that embodied, socially engaging stimuli can significantly enhance MI performance, yielding cleaner EEG data and more reliable BCI control. This contribution not only advances neurorehabilitation and assistive technology but also opens new pathways for human–robot collaboration. Wang’s research is notable for its practical, user-centered approach, bridging cognitive neuroscience and robotics to solve real-world interaction challenges. With growing recognition in the field, Wang’s work is poised to influence next-generation BCI systems that are more intuitive and accessible for users with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1