Shanying Zhu

Tianjin University of Technology

Papers

1

Total Citations

26

H-Index

1

About

Shanying Zhu is a leading researcher in rehabilitation robotics and human–robot interaction, with a primary focus on lower limb exoskeletons and intelligent gait recognition. His most-cited work, “Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion” (2022, 26 citations), addresses critical limitations in clinical rehabilitation by integrating multi-sensor data to improve the accuracy and adaptability of exoskeleton control. Zhu’s research bridges the gap between robotic assistance and natural human movement, advancing interactive information fusion techniques that enable more responsive and personalized rehabilitation therapies. His contributions are particularly impactful for patients with mobility impairments, offering new pathways for restoring walking function through smarter, context-aware exoskeletons. By tackling real-world challenges in sensor fusion and gait phase detection, Zhu has helped shape a more intuitive interface between humans and assistive devices. His work continues to influence both robotic design and clinical practice, making him a notable figure in the growing field of rehabilitation engineering and interactive robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
26
Total Citations
26
Avg Citations/Paper
🏆 Most Cited Paper
Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion
26 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Tianjin University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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