Jinfei Li
Papers
3
Total Citations
46
H-Index
3
About
Jinfei Li is a researcher specializing in robot-assisted rehabilitation, adaptive control systems, and human-robot interaction, with a particular focus on improving outcomes for stroke survivors. His work sits at the compelling intersection of robotics, biomechanics, and clinical therapy, addressing one of healthcare's most pressing challenges: restoring motor function and independence to stroke patients. Li's most influential contribution, "Anxiety Detection and Training Task Adaptation in Robot-Assisted Active Stroke Rehabilitation" (2018, 23 citations), breaks new ground by incorporating emotional state recognition into robotic rehabilitation systems — enabling machines to respond to patients' psychological states much as experienced human therapists would. This humanizing of robotic care represents a significant conceptual leap in the field. His earlier work established equally important foundations. His 2012 paper on adaptive hierarchical control for muscle strength training (12 citations) introduced a biomechanically-informed framework for progressively restoring upper-limb strength, while his 2014 clinical study (11 citations) validated fuzzy-logic-based control algorithms through real patient trials, demonstrating practical therapeutic value. Across his research, Li consistently bridges engineering rigor with clinical applicability, advancing rehabilitation robotics from mechanical tools toward intelligent, patient-responsive systems capable of meaningful therapeutic partnership.
Research Focus
Key Achievements
Top Papers
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