Xuebin Qin

Xi'an University of Science and Technology, Shaanxi University of Science and Technology

Papers

Total Citations

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About

Xuebin Qin is a researcher at the forefront of brain-computer interface (BCI) technology and intelligent robotics, with a focus on translating neural signals into practical control systems. His major contributions lie in developing BCI frameworks that enable direct communication between the human brain and external devices, bypassing damaged neural pathways to assist individuals with motor impairments. Notably, his work on a "coloring and timing BCI for nursing bed robots" (11 citations) demonstrates how EEG-based systems can be integrated into assistive care environments, allowing patients to control robotic beds through cognitive tasks. Qin also pioneered a motor imagery-based method for NAO robot limb control (9 citations), where users manipulate a humanoid robot’s movements using imagined motor actions—a breakthrough for rehabilitation and human-robot interaction. His recent exploration of hybrid path-planning algorithms for mobile robots (2025) extends his expertise into autonomous navigation, combining artificial potential fields with strategic optimization. With over 20 cumulative citations, Qin’s research bridges neuroscience and robotics, offering scalable solutions for healthcare automation and assistive technology. His work is particularly impactful for students and engineers seeking to develop non-invasive, real-world BCI applications that improve quality of life.