Hongbo Liang
Papers
6
Total Citations
26
H-Index
3
About
Hongbo Liang is a robotics and biomedical engineering researcher whose work sits at the intersection of Brain-Machine Interfaces (BMIs), wearable exoskeleton systems, and neural signal processing. His research focuses primarily on harnessing electroencephalography (EEG) signals to enable intuitive, brain-driven control of upper-limb power assistance devices — a challenging frontier that bridges neuroscience and rehabilitation engineering. Liang's most significant contributions center on developing novel methods for estimating electromyography (EMG) signals from EEG data, particularly for the complex multi-degree-of-freedom shoulder joint, advancing the feasibility of hands-free exoskeleton control for both disabled individuals and healthy users seeking physical augmentation. His 2020 study on EEG-based EMG estimation for shoulder power augmentation stands as his most impactful work, accumulating 10 citations, while his broader portfolio across 2017–2018 reflects a sustained and systematic effort to refine motion estimation accuracy and feature extraction from neural signals. Beyond BMI research, Liang has also explored bipedal robotics, examining frictional constraints on walking robot locomotion. With a cumulative citation count reflecting growing recognition in a highly specialized field, his work contributes meaningfully to the future of assistive and augmentative human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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- 6Frictional constraints on the sole of a biped robot when slipping2 citations · 2017