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Research on axial compensation precision puncture control method of prostate puncture robot

  • Li Bing*
  • , Zhu Junwu
  • , Yuan Lipeng
  • *Corresponding author for this work
  • Yangzhou University
  • School of Mechatronics Engineering, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In clinical practice, prostate particle implantation surgery is performed by a robot control puncture needle; it is a safe and effective treatment method for prostate cancer. During surgery, the tissue deformation is caused by interaction forces between the needle and soft tissue, which results in the displacement error between the needle tip and the target point in the axial direction, thus affecting the precision of particle implantation and treatment effect. Therefore, an axial compensation precision puncture control method for prostate puncture robot is proposed in this article. Firstly, the position action relationship between the puncture needle and the target point is analyzed in the needle’s entry into the tissue, and the force analysis is carried out by the biomechanical Kelvin model; the interaction model between the puncture needle and the soft tissue is established, so as to obtain the axial compensation precision puncture control model. Then, an improved adaptive particle swarm optimization (PSO) algorithm based on Levy Flight is proposed to identify parameters of this control model for puncture prostate in this article. Matlab–Adams co-simulation mode is used to simulate and analyze the axial compensation precision puncture control method when the puncture needle enters soft tissue, and thus the optimal parameters of this control model for puncture prostate are obtained. Finally, the experiment of puncture velocity with the axial compensation and comprehensive experiment of axial compensation puncture control method are carried out in combination with the robot. The results of the puncture velocity verification experiment show that when the puncture velocity is 12.3 mm/s, the parameters values (elastic coefficient of 2.165 N/m and damping coefficient of 0.754 Ns/m) obtained by identification are reasonable. In the experimental analysis for parameters identification, bionic soft tissue and pig kidney are used for experimental identification, and the results are basically consistent with the simulation. In the comparison experiment of axial compensation positioning performance, the coincidence degree between the tip of the puncture needle and the designated position reached 80% (higher than 35% of direct puncture). Meanwhile, in the comparison experiment of different puncture depths, the axial puncture deviation is 0.54–0.62 mm when the puncture depth is 50–80 mm, which is significantly smaller than the direct puncture of 1.58–2.15 mm. The experimental results further demonstrate the effectiveness of the axial compensation precision puncture control method proposed in this article and the identification of parameter values, which can better improve the puncture accuracy and ensure the treatment effect of particle implantation for prostate cancer. The contents of this article can provide reference for the research of minimally invasive puncture surgery.

Original languageEnglish
JournalInternational Journal of Advanced Robotic Systems
Volume22
Issue number2
DOIs
StatePublished - 1 Mar 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Bayesian neural network
  • Monte Carlo dropout
  • Parallel manipulator
  • forward geometric model
  • uncertainty
  • variational inference

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