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About

Guopu Zhao is a leading researcher at the intersection of rehabilitation robotics and brain–computer interfaces (BCIs), with a focused mission to restore motor function in stroke survivors. His core contributions lie in designing intelligent, EEG-modulated robotic systems that translate a patient’s motor imagery—the mental rehearsal of movement—into tangible, robot-assisted therapy. Zhao’s seminal 2015 work on a robotic neurorehabilitation system (14 citations) pioneered the integration of motor imagery EEG classification with a robotic arm, enabling the device to respond directly to the user’s neural intent. He further refined this approach in a 2015 study (11 citations) detailing a complete EEG-controlled robot system, and in a 2018 paper (7 citations) that introduced an EEG-triggered upper extremity trainer using the Barrett WAM robot. By prioritizing the patient’s voluntary movement intention, Zhao’s work moves beyond passive robotic therapy toward truly interactive, neurofeedback-driven rehabilitation. His research also extends to autonomous mobile robotics, where he developed a visual servoing method for stair-climbing robots. With a growing citation footprint, Guopu Zhao is a key architect of next-generation, brain-driven neurorehabilitation technologies.