Yanchao Guo, Yimiao Chen, Xianzheng Zhou, Jianping Bi, Jason Z Moore, Qinhe Zhang
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引用次数: 0
Abstract
Background: Minimally invasive internal fixation is the preferred treatment option for femoral shaft fractures. However, there are problems such as invisibility, inaccuracy and instability in the process of plate implantation.
Methods: In this paper, a dual-mode robot-assisted plate implantation method was proposed by combining a starting point determination algorithm, motion capture, deep learning and robotics.
Results: The neural network model planned the plate implantation trajectory according to patient's condition. Then, the advantages of high stability and high precision of the robotic arm were used for plate implantation.
Conclusion: The trend and fluctuation of the plate implantation trajectories obtained using this method met clinical requirements. Furthermore, the robotic arm implantation process was safe.