Jieying He

Fudan University

Papers

1

Total Citations

12

H-Index

1

About

Jieying He’s research lies at the intersection of rehabilitation robotics and human–robot interaction, with a focus on developing intelligent, adaptive systems for neurorehabilitation. Her most cited work, “Customizing Robot‐Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism” (2021, 12 citations), addresses a critical gap in stroke recovery: the need for personalized passive movement therapy for early-stage or severely paralyzed patients. He proposes a novel framework that enables upper-extremity robots to learn from therapists’ manual guidance, effectively “teaching” the robot to replicate customized, patient-specific exercises. This approach moves beyond one-size-fits-all protocols, allowing for real-time adaptation to individual patient needs and improving therapeutic outcomes. By integrating teaching–training mechanisms into robotic assistance, He’s work bridges clinical expertise with automation, offering a scalable solution for rehabilitation clinics. Her contributions are particularly impactful for stroke survivors who cannot actively participate in therapy, ensuring they still receive tailored, high-quality care. With a growing citation record, He is establishing herself as a key voice in the field of assistive robotics, where her innovations promise to make robot-assisted therapy more intuitive, effective, and widely accessible.

Research Focus

Key Achievements

1
H-Index
1
Papers
12
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Customizing Robot‐Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism
12 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Fudan University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago