Papers

3

Total Citations

176

H-Index

3

About

Dr. Haiqing Zheng is a leading researcher in rehabilitation robotics and human–machine interaction, with a focus on restoring motor function after stroke. Her work centers on two critical challenges: enabling safe, effective robot-assisted rehabilitation and automatically detecting and reducing compensatory movements that can hinder long-term recovery. In her highly cited 2019 study (112 citations), Dr. Zheng developed a support vector machine (SVM) classifier for surface electromyography (sEMG) signals, enabling intuitive control of upper-limb rehabilitation robots for self-training. She further advanced the field by pioneering real-time compensation detection systems, using pressure distribution sensors to identify and alert patients to maladaptive trunk movements during reaching tasks—work published in 2020 (39 and 25 citations). These contributions are foundational for creating intelligent, patient-cooperative rehabilitation systems that can match or exceed the quality of therapist-led therapy. Dr. Zheng’s research directly addresses the gap in unsupervised home-based rehabilitation, offering scalable solutions that promote correct movement patterns and improve functional outcomes for stroke survivors.

Research Focus

Key Achievements

3
H-Index
3
Papers
176
Total Citations
59
Avg Citations/Paper
🏆 Most Cited Paper
SVM-Based Classification of sEMG Signals for Upper-Limb Self-Rehabilitation Training
112 citations · 2019
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago