Min Zhan

University of Maryland, Baltimore

Papers

4

Total Citations

228

H-Index

4

About

Min Zhan’s research lies at the intersection of neurorehabilitation, robotics, and motor recovery after stroke. Her work has fundamentally advanced our understanding of how technology-assisted therapy can restore upper extremity function in chronic stroke survivors. In her landmark 2011 randomized trial (121 citations), Zhan demonstrated that gravity-compensating robotic training significantly improves arm motor control, establishing a critical link between mechanical support and neural recovery. She further showed that adding transition-to-task practice to robot-assisted training enhances real-world functional gains (80 citations), addressing a longstanding gap between laboratory improvements and daily-life performance. Zhan has also pioneered the use of multimodal biomarkers—including kinematic, neurophysiological, and genetic data—to predict individual responses to repetitive task practice. Her 2022 study (18 citations) identified baseline predictors of meaningful impairment reduction, offering a path toward personalized rehabilitation. By integrating robotics, predictive modeling, and rigorous clinical trial design, Zhan has shaped how clinicians and engineers approach post-stroke motor recovery, making her a leading voice in evidence-based neurorehabilitation.

Research Focus

Key Achievements

4
H-Index
4
Papers
228
Total Citations
57
Avg Citations/Paper
🏆 Most Cited Paper
Effect of Gravity on Robot-Assisted Motor Training After Chronic Stroke: A Randomized Trial
121 citations · 2011
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Maryland, Baltimore

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago