Papers

7

Total Citations

141

H-Index

5

About

Moon Suk Bang is a leading researcher in assistive robotics and brain-machine interfaces (BMI), with a focus on restoring motor function for individuals with disabilities. Her work bridges non-invasive neural signal processing and robotic hardware design to create practical, user-centered assistive technologies. Bang’s most cited study (2015, 41 citations) pioneered the prediction of three-dimensional robot arm trajectories from non-invasive neural signals, demonstrating a viable alternative to invasive BMI approaches. She further advanced the field by developing a vision-aided BMI training system for robotic arm control, successfully tested on two patients with cervical spinal cord injury (2019, 20 citations). Bang has also made significant contributions to rehabilitation robotics through motion characterization using inertial measurement units (IMU) for activities of daily living (2019, 33 citations) and by investigating user perspectives on external robotic arms versus upper limb exoskeletons (2019, 20 citations). Her work on path planning algorithms for autonomous electric wheelchairs (2020, 20 citations) extends her impact to mobility assistance. With over 140 total citations, Bang’s research is notable for its emphasis on user needs and clinical applicability, making her a key figure in the development of non-invasive, accessible assistive technologies.

Research Focus

Key Achievements

5
H-Index
7
Papers
141
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals
41 citations · 2015
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Seoul National University Hospital, Seoul National University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago