Papers
2
Total Citations
28
H-Index
2
About
Xuquan Ji is at the forefront of spinal surgical robotics, with a focused research program dedicated to advancing autonomous bone-cutting procedures. His primary contributions lie in the development and validation of the first autonomous robotic system for laminectomy, a critical spinal decompression surgery traditionally reliant on manual skill. Ji’s landmark 2023 study, which has garnered 25 citations, provides the first accuracy evaluation of a robotic system designed specifically for autonomous laminectomy in thoracic and lumbar vertebrae, moving beyond the field’s prior emphasis on pedicle screw placement. To enhance the safety of such autonomous cutting, Ji has also pioneered the use of electrical impedance monitoring combined with a Long Short-Term Memory Fully Convolutional Network (LSTM-FCN) for real-time breakthrough prediction during robotic laminectomy with ultrasonic osteotomes. This work, published in 2022, addresses a key barrier to clinical adoption by enabling the robot to distinguish between bone and soft tissue, thereby preventing inadvertent dural or nerve injury. Ji’s research is notable for its direct translational impact, bridging the gap between mechatronic design and intraoperative safety monitoring, and establishing a new paradigm for autonomous execution of high-risk spinal procedures.
Research Focus
Key Achievements
Top Papers
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