Yujian Zhang
Papers
3
Total Citations
9
H-Index
2
About
Yujian Zhang is a rising researcher in neurorehabilitation engineering, with a focused expertise in developing brain-computer interfaces (BCI) and robotic exoskeletons to restore motor function in stroke patients. His work centers on two critical challenges: enhancing motor imagery (MI) for lower limb recovery and integrating functional electrical stimulation (FES) with wearable robotics. Zhang’s major contribution lies in designing novel, multi-modal stimulation paradigms that make abstract MI tasks more intuitive and effective. For instance, his 2024 study validated that gait-phase encoding sensory electrical stimulation can significantly improve EEG signal discriminability in stroke patients, a breakthrough for BCI-based therapy. His 2022 paper on a trajectory-adaptive FES-exoskeleton strategy demonstrated a path toward restoring natural, coordinated gait, addressing a key limitation in current hybrid rehabilitation systems. While his most-cited works currently hold 2–4 citations, reflecting the early stage of his career, these publications represent foundational steps in a rapidly growing field. Zhang’s research is notable for its direct clinical applicability, aiming to bridge the gap between laboratory BCI systems and practical, patient-friendly rehabilitation tools that can be deployed in real-world therapy settings.
Research Focus
Key Achievements
Top Papers
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