Hyeokjun Kwon

Papers

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About

Hyeokjun Kwon is a leading researcher in brain-machine interfaces (BMIs) and assistive robotics, with a focus on non-invasive neural control systems. His most cited work, "Wireless brain-machine interface using EEG and EOG: brain wave classification and robot control" (2012, 13 citations), pioneered a hybrid approach combining electroencephalography (EEG) and electrooculography (EOG) signals for real-time robot control. This study demonstrated how users could wirelessly command external devices using only thought and eye movements, significantly advancing the design of assistive technologies for individuals with severe motor disabilities. Kwon’s contributions lie in developing robust classification algorithms that translate neural signals into precise machine commands, bridging the gap between human intent and robotic action. His work has been instrumental in making BMIs more practical and accessible, with applications ranging from wheelchair navigation to prosthetic limb control. By integrating wireless communication and multimodal neural sensing, Kwon has helped shape the future of human-robot interaction, offering new possibilities for restoring mobility and independence to those with paralysis or neuromuscular disorders.