Byoung-Hee Kwon

Korea University

Papers

1

Total Citations

76

H-Index

1

About

Byoung-Hee Kwon is a researcher specializing in brain-computer interfaces (BCIs) and human-machine interaction, with a particular focus on non-invasive neural signal acquisition and upper extremity motor control. His most recognized contribution is the development and publication of a comprehensive multimodal signal dataset capturing 11 intuitive movement tasks from the upper extremity across multiple recording sessions, published in 2020 and accumulating 76 citations — a testament to its utility within the BCI and rehabilitation engineering communities. This work addresses a critical challenge in BCI research: achieving natural, intuitive communication between users and robotic systems without relying on artificial command-matching paradigms. By providing a richly annotated, multi-session dataset, Kwon has offered the research community a valuable benchmark resource for developing and validating movement decoding algorithms. His efforts contribute meaningfully to advancing prosthetics, assistive robotics, and neurorehabilitation technologies. Researchers and students exploring motor intention decoding, signal processing, or neuroprosthetic control will find his dataset an essential foundation for reproducible, rigorous experimental work in the field.

Research Focus

Key Achievements

1
H-Index
1
Papers
76
Total Citations
76
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal signal dataset for 11 intuitive movement tasks from single upper extremity during multiple recording sessions
76 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Korea University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago