Papers
19
Total Citations
263
H-Index
11
About
Lizheng Pan is a prominent researcher specializing in robot-assisted neurorehabilitation, brain-computer interfaces, and adaptive control systems for stroke recovery. His work sits at the critical intersection of robotics, neuroscience, and clinical therapy, focusing primarily on restoring upper-limb function in stroke survivors — one of the world's leading causes of long-term disability. Pan's most significant contributions include developing sophisticated EEG-based motor imagery systems that allow rehabilitation robots to respond directly to patients' neural activity, effectively bridging mind and machine in therapeutic settings. His 2011 paper on motor imagery EEG-driven robotic rehabilitation (39 citations) and subsequent 2015 neurorehabilitation system design exemplify this pioneering integration. Equally influential is his work on impedance control and adaptive motion strategies, ensuring robots respond safely and intelligently to each patient's changing biomechanical condition. A recurring theme across Pan's research is patient safety and personalization. He has developed hierarchical safety supervisory frameworks, fuzzy-logic control methods, and anxiety-detection algorithms that enable rehabilitation systems to adapt to patients' emotional and physical states in real time. With over 200 cumulative citations and clinically validated methodologies, Pan's research has meaningfully advanced the field toward truly intelligent, patient-centered rehabilitation robotics.
Research Focus
Key Achievements
Top Papers
- 1Robot-Aided Upper-Limb Rehabilitation Based on Motor Imagery EEG39 citations · 2011
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- 8Robotic neurorehabilitation system design for stroke patients14 citations · 2015
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