Papers
12
Total Citations
212
H-Index
8
About
Jin Hu is a robotics and biomedical engineering researcher whose work sits at the intersection of rehabilitation robotics, neural signal processing, and human-machine interfaces. He is best known for developing the **iLeg**, a lower limb exoskeleton rehabilitation robot designed to assist patients with hemiplegia and paraplegia, which has garnered 64 citations and stands as his most influential contribution to the field. His research systematically addresses the full pipeline of rehabilitation robotics: from mechanical design and impedance-based control strategies to sophisticated biosignal-driven interfaces. Hu's work on training strategies using impedance control — encompassing passive, damping-active, and spring-active modalities — has shaped how clinicians and engineers think about adaptive robot-assisted therapy. He has further advanced the field by integrating functional electrical stimulation (FES) with robotic control, and by leveraging surface electromyography (sEMG) and electroencephalogram (EEG) signals to decode user intent, enabling more responsive and patient-driven rehabilitation systems. His application of spiking neural networks (SNN) to EEG classification reflects a forward-thinking approach to neural computation. With over 200 cumulative citations, Hu's body of work offers students a rigorous, clinically motivated roadmap for intelligent rehabilitation technology.
Research Focus
Key Achievements
Top Papers
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- 4sEMG-based torque estimation for robot-assisted lower limb rehabilitation20 citations · 2015
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- 6SEMG feature extraction methods for pattern recognition of upper limbs17 citations · 2011
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- 10A flying-insect-inspired hybrid robot for disaster exploration7 citations · 2017