Global Workflow of a Comanipulation-Based Robotic System for Cervical Spine Surgery.
Authors
Affiliations (7)
Affiliations (7)
- Department of GMSC, Pprime Institute CNRS, ENSMA, University of Poitiers, UPR 3346, Poitiers, France.
- Nantes University, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes, France.
- Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan.
- Graduate Institute of Biomedical Electronics & Bioinformatics, National Taiwan University, Taipei, Taiwan.
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan.
- National Central University, Taoyuan City, Taiwan.
- ABS Laboratory, College of Medicine and Pharmacy, University of Poitiers, Poitiers, France.
Abstract
Cervical arthrodesis requires precise pedicle screw placement to ensure safety and effectiveness. Traditional planning and execution are time-consuming and prone to variability. We developed a robot-assisted system integrating three components: an AI-based preoperative planning module, adapted from previous work, to generate patient-specific screw trajectory from 3D CT point-clouds; an intraoperative registration and motion compensation system with optical tracking to align the trajectory with patient anatomy in real time; and a comanipulation control strategy enforcing virtual fixtures and depth limits to guide the robotic arm safely. The system was tested on 3D-printed models and cadaveric specimens. Robotic assistance significantly improved the geometric accuracy of drilling, reducing transverse positional deviations by a factor of two and orientation deviations by a factor of eight compared with freehand procedures. In addition, the average drilling depth overshoot was reduced by 50%. Perforation rates were found to be of the same order as those observed with freehand techniques. The proposed workflow improves trajectory-following accuracy and depth control while preserving intuitive surgeon interaction. These results demonstrate the feasibility of integrating AI-based planning, intraoperative tracking, and collaborative robotics for cervical spine surgery.