Papers

1

Total Citations

13

H-Index

1

About

Qingyun Meng is a leading researcher in the fields of neural rehabilitation engineering and human-robot interaction, with a particular focus on how the brain adapts to and benefits from robotic-assisted therapy. Their most-cited work, "The identification of interacting brain networks during robot-assisted training with multimodal stimulation" (2022, 13 citations), represents a significant contribution to understanding the neural mechanisms underlying rehabilitation. In this landmark study, Meng pioneered the use of multimodal stimulation—combining visual and auditory cues with robotic movement—to map how distinct brain networks coordinate during motor training. This work has been instrumental in demonstrating that robot-assisted therapy does more than just guide physical movement; it actively reshapes neural connectivity, offering a scientific foundation for more effective, personalized rehabilitation protocols. By bridging neuroscience and robotics, Meng’s research has opened new avenues for designing smarter rehabilitation systems that adapt to a patient’s brain state, ultimately improving recovery outcomes for those with central nervous system injuries. Their findings continue to influence both clinical practice and the development of next-generation neurorehabilitation technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
13
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
The identification of interacting brain networks during robot-assisted training with multimodal stimulation
13 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Shanghai University of Medicine and Health Sciences

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago