Papers

4

Total Citations

37

H-Index

3

About

Fo Hu’s research lies at the dynamic intersection of soft robotics, brain-computer interfaces (BCI), and human-robot interaction. His work is distinguished by a focus on creating more intuitive and safer robotic systems that can be controlled by human physiological signals. A key contribution is the development of a fiber-reinforced, human-like soft robotic manipulator that uses surface electromyography (sEMG) for force estimation, a design that has garnered 16 citations for its potential in assistive technologies. Hu has also made significant strides in BCI, notably by pioneering a method to decode both voluntary and involuntary upper-limb motor imagery using graph Fourier transform and cross-frequency coupling coefficients (15 citations). This work directly addresses a major challenge in BCI for stroke rehabilitation and robot control. Furthermore, his research into movement authorization strategies for service robots, which monitors human attention to ensure safety, demonstrates a comprehensive approach to human-robot interaction security. Hu’s portfolio, including his work on a humanoid soft hand controlled by sEMG, showcases a dedicated effort to bridge the gap between human intent and robotic action, with a clear impact on the future of assistive and collaborative robotics.

Research Focus

Key Achievements

3
H-Index
4
Papers
37
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A fiber-reinforced human-like soft robotic manipulator based on sEMG force estimation
16 citations · 2019
📈 Most Prolific Year: 2018 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Northeastern University, North Eastern University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago