Yuze Jiao

University of Chinese Academy of Sciences, Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yuze Jiao is a researcher advancing the frontiers of neural rehabilitation robotics, with a focus on restoring motor function for paralyzed patients. Their work centers on two critical challenges: decoding human motion intention and enhancing proprioceptive feedback during robot-assisted therapy. In their highly cited 2021 study, Jiao pioneered a CNN-LSTM network that predicts human joint angles by fusing multi-band surface electromyography (SEMG) signals with historical angle data—a method that enables safer, more responsive active rehabilitation training. This work has garnered 7 citations, reflecting its influence on intention-driven robotic control. More recently, Jiao’s 2024 paper introduced a dynamic electrical stimulation technique to amplify proprioception during robot-assisted neural rehabilitation, validated through EEG analysis. With 4 citations already, this innovative approach addresses the critical gap of weak sensory feedback in current therapies, potentially accelerating neural reorganization. Jiao’s contributions bridge machine learning, neurophysiology, and robotics, offering practical solutions for personalized, effective rehabilitation. Their research is essential reading for engineers and clinicians developing next-generation assistive technologies that restore both movement and sensory awareness in stroke and spinal cord injury patients.