Max Robotics — Global Service Robot Directory + US Certification

About

Chun Kee Chung is a pioneering researcher at the intersection of neuroscience and engineering, whose work focuses on developing brain-machine interfaces (BMIs) to restore motor function for individuals with disabilities. His key research areas include motor imagery decoding, non-invasive neural signal processing, and closed-loop somatosensory feedback systems. Chung’s most impactful contribution is his characterization of kinesthetic versus visual motor imagery, a foundational study (80 citations) that enables more robust control of robotic arms for paralyzed patients. He further advanced the field by demonstrating that three-dimensional reaching trajectories could be predicted from non-invasive magnetoencephalography signals, achieving 41 citations for his robot arm study. Notably, his application of LSTM deep learning models improved trajectory prediction accuracy (21 citations), addressing a critical challenge in real-time BMI control. Chung has also explored artificial somatosensation through dynamic cortical stimulation, a key step toward closed-loop systems that provide sensory feedback. His work spans from non-invasive to less-invasive technologies, culminating in integrated robot arm-gripper systems. With over 160 total citations, Chung’s research bridges fundamental neuroscience and practical rehabilitation engineering, offering hope for restoring lost motor and sensory functions.