Papers
3
Total Citations
15
H-Index
3
About
Rongkai Liu is an emerging researcher specializing in human motion analysis, wearable robotics, and rehabilitation engineering, with a particular focus on gait recognition and exoskeleton-assisted locomotion. His work addresses a critical challenge in human-robot interaction: achieving precise, real-time understanding of human movement to enable intelligent assistive devices. Liu's most significant contribution lies in developing advanced gait phase recognition frameworks that leverage multi-source information fusion. His 2022 paper on this topic, which has garnered 8 citations, introduced algorithms capable of accurately detecting gait phases — a foundational requirement for controlling exoskeleton robots effectively. Building on this, his subsequent research explored flexible sensor fusion for real-time gait phase estimation, prioritizing portability and user-friendliness in wearable systems. A particularly noteworthy aspect of Liu's work is his attention to clinical rehabilitation applications. His research on adaptive symmetry reference trajectory generation for active knee orthoses directly addresses the needs of hemiplegic patients, using motion data from an unaffected limb to guide rehabilitation of the impaired side. Collectively accumulating over 15 citations within just two years, Liu's contributions are establishing a meaningful foundation for the next generation of intelligent rehabilitation robotics.
Research Focus
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