Papers
11
Total Citations
147
H-Index
7
About
Sujiao Li is a prominent researcher specializing in rehabilitation robotics, human-robot interaction, and neural engineering, with a particular focus on upper limb rehabilitation systems for stroke and neurologically impaired patients. Their work bridges cutting-edge robotics with neuroscientific evaluation, employing functional near-infrared spectroscopy (fNIRS) to investigate cortical activation patterns during robot-assisted training—a methodological contribution that has advanced understanding of how different training modalities engage the brain. Li's influential 2023 systematic review on intent recognition in rehabilitation robots (40 citations) has become a foundational reference in the field, while their investigations into passive versus active training modes and multi-sensory virtual reality interactions have meaningfully informed clinical rehabilitation protocols. Their engineering contributions include designing wheelchair-integrated upper limb exoskeletons and developing EMG-based motion compensation and torque prediction systems that enable robots to respond dynamically to patients' movement intentions. With over 145 cumulative citations across a decade of work, Li has also explored skin detection for assistive bathing robots and quantitative kinematic assessment tools, demonstrating a broad commitment to intelligent assistive technologies that enhance independence and quality of life for aging and disabled populations.
Research Focus
Key Achievements
Top Papers
- 1Research of intent recognition in rehabilitation robots: a systematic review40 citations · 2023
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