Zhaokang Chen

Hong Kong University of Science and Technology

Papers

Total Citations

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About

Zhaokang Chen is a leading researcher in brain-computer interfaces (BCIs) and assistive robotics, with a focus on integrating neural and ocular signals for real-world control systems. His most cited work, "Hybrid gaze/EEG brain computer interface for robot arm control on a pick and place task" (2015, 53 citations), introduces a pioneering hybrid BCI that fuses eye-tracking data with electroencephalography (EEG) to enable intuitive, high-precision control of a robotic arm. By allowing users to command the end effector in four directions through motor imagery, Chen’s system significantly enhances the speed and accuracy of pick-and-place tasks, addressing critical limitations of single-modality BCIs. This contribution has been influential in advancing non-invasive assistive technologies for individuals with severe motor impairments, bridging the gap between human intent and machine action. Chen’s work demonstrates a deep commitment to practical, user-centered design, with his hybrid approach serving as a foundational model for subsequent research in multimodal neural interfaces. His achievements underscore the potential of combining gaze and brain signals to create more responsive and accessible robotic systems, marking him as a key innovator in the field of neuroprosthetics.