Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot

Xingyu Chen, Yinan Chen, Wenke Duan, Toluwanimi Oluwadara Akinyemi, Guanlin Yi, Jie Jiang, Wenjing Du, Olatunji Mumini Omisore

Research output: Journal PublicationArticlepeer-review

4 Citations (Scopus)


Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.

Original languageEnglish
Article number106
Issue number12
Publication statusPublished - Dec 2022
Externally publishedYes


  • endovascular catheterization
  • force feedback
  • learning-based models
  • vascular interventional surgical robot

ASJC Scopus subject areas

  • Ceramics and Composites
  • Civil and Structural Engineering
  • Biomaterials
  • Mechanics of Materials


Dive into the research topics of 'Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot'. Together they form a unique fingerprint.

Cite this