About

Yongxiang Zou is a leading researcher at the intersection of biomimetic robotics, human–machine interaction, and rehabilitation engineering. His work centers on developing intelligent, personalized assistive technologies—particularly wearable exoskeletons and hand rehabilitation robots—that draw inspiration from the human musculoskeletal system. Zou’s most cited paper (31 citations) introduces a multimodal fusion model combining surface electromyography and ultrasound signals to estimate human hand force, a critical advance for safe human–robot collaboration. He has also pioneered a bioinspired triboelectric soft pneumatic actuator for post-stroke spasticity assessment (26 citations), addressing a long-standing clinical challenge. His hierarchical optimization framework for personalized hand and wrist musculoskeletal modeling (14 citations) enables more accurate motion estimation, while his work on physics-informed deep transfer learning and Lyapunov-stable dynamic systems pushes the boundaries of learning from demonstration. With recent publications in 2024–2025, Zou’s research is rapidly gaining traction, offering transformative solutions for exoskeleton control, rehabilitation robotics, and intuitive human–computer interfaces.

Research Focus

Key Achievements

4
H-Index
7
Papers
83
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
A Multimodal Fusion Model for Estimating Human Hand Force: Comparing surface electromyography and ultrasound signals
31 citations · 2022
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Beijing Academy of Artificial Intelligence, Chinese Academy of Sciences, University of Chinese Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago