Linhang Ju
Papers
5
Total Citations
110
H-Index
5
About
Linhang Ju is a leading researcher in the field of rehabilitation robotics and human–robot interaction, with a focus on developing intelligent, adaptive systems for lower-limb assistance. His work centers on three key areas: adaptive control of rehabilitation robots, locomotion mode recognition for robotic prostheses, and novel wearable sensing technologies. Ju’s major contributions include the development of a human-centred adaptive control framework for lower-limb rehabilitation robots, which uses a human–robot interaction dynamic model to improve safety and effectiveness—a work that has garnered 72 citations. He also pioneered the Small-Data-Driven Temporal Convolutional Capsule Network (TCCN) for precise locomotion mode recognition in robotic prostheses, addressing a critical challenge in prosthetic control under varied walking conditions. Additionally, Ju has advanced anti-disturbance sliding mode control for variable stiffness actuators and introduced innovative fiber-optic sensors, such as the carbon-optic fiber (COF) twisted sensor and semiring-optic-fiber (SROF) sensor, for noncontact muscle activity and gait monitoring. His sensor work, with 9 citations each, demonstrates significant potential for wearable robotics. Ju’s research is notable for its interdisciplinary approach, combining control theory, machine learning, and sensor engineering to enhance the quality of life for neurologically disabled patients.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5