Sung Woo Park

Papers

Total Citations

H-Index

About

Sung Woo Park is a leading researcher in brain-machine interfaces (BMI) and assistive robotics, with a focus on non-invasive neural signal processing. His seminal work, "A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals" (2015, 41 citations), pioneered the use of non-invasive electroencephalography (EEG) to control robotic arms in three-dimensional space—a significant leap from invasive methods. By demonstrating that high-dimensional motor commands could be decoded from scalp-recorded brain activity, Park challenged the prevailing reliance on implanted electrodes, offering a safer, more accessible path for restoring motor function in individuals with paralysis. His contributions bridge computational neuroscience and rehabilitation engineering, showing that non-invasive BMI can achieve practical, real-time control of complex devices. This work has influenced subsequent efforts to reduce the invasiveness of neural prosthetics while maintaining performance, making him a key figure in translating BMI technology from lab to clinic. Park’s research continues to push the boundaries of how brain signals can replace lost motor functions, with his citation record reflecting growing interest in his approach.