Xingmin Guan

Papers

Total Citations

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About

Xingmin Guan is a researcher at the forefront of surgical robotics and human–machine interaction, with a particular focus on the cognitive and perceptual challenges that arise in minimally invasive procedures. His most-cited work, "Visual–perceptual mismatch in robotic surgery" (2016, 34 citations), addresses a critical bottleneck in robotic-assisted surgery: the disconnect between a surgeon’s visual input and their proprioceptive feedback. This foundational paper has helped define a key area of ergonomic research, influencing the design of more intuitive robotic interfaces and training protocols. Guan’s contributions are instrumental in improving surgical precision and reducing cognitive load, directly impacting patient safety and surgeon performance. His work bridges engineering, psychology, and clinical practice, making him a vital voice in the evolution of next-generation surgical systems. With his research cited by peers in both robotics and medical simulation, Guan continues to shape how we understand and optimize the human–robot partnership in the operating room.