Papers

2

Total Citations

137

H-Index

2

About

Shenghong He is a leading researcher in the field of assistive robotics and brain-computer interfaces (BCIs), with a primary focus on restoring mobility and independence to individuals with severe motor disabilities. His major contributions lie in the development of hybrid BCIs that integrate electroencephalography (EEG) and electrooculography (EOG) signals to control complex, multi-functional assistive systems. Notably, his 2019 work on an EEG-/EOG-based hybrid BCI for controlling an integrated wheelchair robotic arm system (97 citations) addressed a critical gap in the field by enabling users to operate both a wheelchair and a robotic arm simultaneously, a task previously limited to single-device control. He further advanced this area with a study on an EOG-based wheelchair robotic arm system specifically designed to help patients with severe spinal cord injuries perform self-drinking tasks (40 citations). By tackling the challenge of precise wheelchair positioning to interact with randomly located objects, He’s research has demonstrated practical, real-world applications of BCI technology. His work is highly influential, providing a foundational framework for the next generation of integrated assistive robots that promise to dramatically improve quality of life for those with profound physical limitations.

Research Focus

Key Achievements

2
H-Index
2
Papers
137
Total Citations
69
Avg Citations/Paper
🏆 Most Cited Paper
An EEG-/EOG-Based Hybrid Brain-Computer Interface: Application on Controlling an Integrated Wheelchair Robotic Arm System
97 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Oxford, South China University of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago