Abstract
Accurate needle insertion is an important task in many medical procedures. This paper studies the case of an autonomous needle insertion system for central venous access, which is a risky and challenging procedure involving the simultaneous manipulation of an ultrasound probe and of a catheterization needle. The goal of this medical operation is to provide access to a deep central vein, which is a key step in cardiovascular treatments or for the administration of drugs and treatments for cancer or infections. Accordingly, in this work we propose an autonomous dual-arm system for central venous access. The system is composed of two Franka robotic arms that are precisely co-registered and collaborate to achieve accurate needle insertion by combining ultrasound and bioimpedance sensing to ensure robust deep vessels visualization and venipuncture detection. The proposed system performance is evaluated on a phantom trainer through experiments simulating the jugular vein access for cardiac catheterization purposes. Quantitative results show the system is able to autonomously scan the area of interest, localize the vein and perform autonomous needle insertion with high accuracy and placement error below 1.7mm, proving the potential of the technology for real clinical use.
Original language | English |
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Title of host publication | 2023 IEEE International Conference on Robotics and Automation (ICRA) |
Publisher | IEEE |
Pages | 4648-4653 |
Number of pages | 6 |
ISBN (Electronic) | 9798350323658 |
DOIs | |
Publication status | Published - 4 Jul 2023 |
Event | 2023 IEEE International Conference on Robotics and Automation - London, United Kingdom Duration: 29 May 2023 → 2 Jun 2023 |
Conference
Conference | 2023 IEEE International Conference on Robotics and Automation |
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Abbreviated title | ICRA 2023 |
Country/Territory | United Kingdom |
City | London |
Period | 29/05/23 → 2/06/23 |
Keywords
- bioimpedance sensing
- dual-robot
- robotic vascular access
- ultrasound-guided
- vessel segmentation
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Artificial Intelligence