Papers
10
Total Citations
84
H-Index
6
About
Xianglong Wan’s research lies at the intersection of rehabilitation robotics, human-robot interaction, and biomechanical optimization. He is best known for developing sensing systems that monitor contact behavior between exoskeletons and skin—critical for preventing pressure injuries during assisted walking. His 2020 paper on monitoring contact behavior with a lower limb exoskeleton (22 citations) introduced a novel sensing cuff that measures interaction forces, directly addressing a key safety concern in long-term exoskeleton use. Wan has also made significant contributions to legged robot locomotion, including optimal landing motions that minimize impact forces and joint torques (12–13 citations), and the counterintuitive use of singular configurations to pull heavy objects with small joint torques (13 citations). His work extends to gait analysis with robotic walkers, where he has shown how these devices alter gait dynamics determinism, informing more natural rehabilitation strategies. Across his most-cited papers, Wan’s research consistently bridges fundamental robotics theory—such as optimization of jumping and landing motions—with practical, user-centered design for assistive devices, making his work valuable for both roboticists and clinicians developing safer, more effective mobility aids.
Research Focus
Key Achievements
Top Papers
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- 4Gait-phase-dependent control using a smart walker for physical training7 citations · 2019
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