Papers

3

Total Citations

24

H-Index

2

About

Guoxin Pan is a leading researcher in rehabilitation robotics, with a primary focus on developing intelligent, bio-signal-driven systems for motor recovery in stroke and hemiplegic patients. His work centers on the intersection of surface electromyography (sEMG) signal processing, pattern recognition, and robotic exoskeleton control. Pan’s major contributions include pioneering methods for sEMG-based shoulder-elbow composite motion pattern recognition, enabling more natural and intuitive control of upper limb rehabilitation robots. He designed a hemiplegic upper limb training system that supports both single and multi-degree-of-freedom movements, significantly advancing patient-specific therapy. His most cited papers, each garnering 11 citations, establish foundational techniques for fusing autoregressive models with wavelet coefficients to decode muscle intent. Pan also contributed to lower limb rehabilitation by designing a robot based on Body Weight Support Treadmill Training (BWSTT), addressing key clinical limitations in existing devices. His work is instrumental in bridging the gap between human physiology and robotic assistance, offering scalable, adaptive solutions for neurorehabilitation. With a clear impact on both engineering design and clinical practice, Pan’s research continues to shape the future of assistive robotics.

Research Focus

Key Achievements

2
H-Index
3
Papers
24
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot
11 citations · 2018
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: National Research Center for Rehabilitation Technical Aids

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago