Zhenlan Li
Papers
4
Total Citations
132
H-Index
4
About
Zhenlan Li is a leading researcher in neurorehabilitation engineering, specializing in the intersection of robotics, neural signal processing, and motor recovery for patients with neurological disorders. Her work centers on developing intelligent rehabilitation systems for stroke and multiple sclerosis patients, with a particular focus on restoring hand and finger function. Li’s major contributions include demonstrating through a randomized controlled trial (50 citations) that task-oriented training assisted by a force-feedback hand rehabilitation robot significantly improves finger grasping function in stroke patients with hemiplegia—a condition affecting over 80% of stroke survivors. She has also advanced the field of myoelectric control by combining feature selection with incremental transfer learning (30 citations), solving the critical problem of electrode shift that degrades EMG pattern recognition in repeated uses of prostheses and rehab robots. Additionally, Li has pioneered a rope-driven flexible hand rehabilitation robot integrated with EEG signal analysis (15 citations), enabling brain-machine interface-based therapy. Her comprehensive review on multiple sclerosis rehabilitation (37 citations) further underscores her commitment to addressing complex neurological deficits. With over 130 total citations, Li’s work bridges robotics, machine learning, and clinical practice, offering tangible solutions for restoring independence in daily living activities.
Research Focus
Key Achievements
Top Papers
- 1
- 2Rehabilitation treatment of multiple sclerosis37 citations · 2023
- 3
- 4