Papers

2

Total Citations

142

H-Index

2

About

Yanqing Xiao is a researcher specializing in the intersection of brain-computer interface (BCI) technology, human-machine interaction, and soft robotics, with a particular focus on motor rehabilitation engineering. Their work addresses one of the most pressing challenges in assistive technology: enabling stroke survivors and individuals with motor impairments to regain functional independence through innovative neural and physical interfaces. Xiao's most significant contribution is the development of a multimodal human-machine interface that integrates EEG, EMG, and EOG signals to enable real-time control of a soft robotic hand — a landmark study published in 2019 that has garnered 140 citations, reflecting its substantial influence within the rehabilitation robotics and BCI communities. This work advanced the field by expanding the repertoire of control commands available to BCI systems, a longstanding technical limitation. Complementing this, earlier research introduced an isometric and isotonic soft hand for rehabilitation paired with noninvasive brain-machine interfaces, demonstrating Xiao's commitment to designing comprehensive, patient-centered solutions that go beyond rigid, conventional rehabilitation devices. Together, these contributions position Xiao as a meaningful contributor to the emerging field of intelligent, neurally-driven rehabilitation robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
142
Total Citations
71
Avg Citations/Paper
🏆 Most Cited Paper
An EEG/EMG/EOG-Based Multimodal Human-Machine Interface to Real-Time Control of a Soft Robot Hand
140 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Beihang University, Beijing Tsinghua Chang Gung Hospital

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago