Abstract
Endovascular surgery has become a popular minimally invasive approach to diagnose and treat various vascular diseases. However, manipulating conventional passive guidewires and catheters still has technical challenges, such as long duration and undesired trauma. In addition, radiation exposure induced by commonly used fluoroscopic imaging has safety concerns. This letter presents a workflow that performs magnetic control of a steerable guidewire under ultrasound (US) guidance to address these issues. The designed magnetically steerable guidewire is fabricated by replica molding method, then a computational-efficient kinematic model is proposed to describe the relationship between the applied magnetic field and tip deformation. The constructed magnetic actuation system integrates three electromagnets and a US probe into a parallel mechanism, realizing large-workspace magnetic field generation and US feedback. Further, a motorized feeder is incorporated to provide the forward and backward motion of the guidewire. An autonomous control framework is proposed consisting of preoperative and intraoperative stages, through which the guidewire can be delivered to the targeted region automatically. Results show that the proposed kinematic model efficiently estimates the deformation of the guidewire. Furthermore, the overall procedure is experimentally validated on a phantom mimicking vascular structures. This letter provides a preliminary robotic solution to improve catheterization procedures by introducing magnetic actuation and US imaging.
| Original language | English |
|---|---|
| Pages (from-to) | 1280-1287 |
| Number of pages | 8 |
| Journal | IEEE Robotics and Automation Letters |
| Volume | 6 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Apr 2021 |
| Externally published | Yes |
Keywords
- automation at small scale
- Magnetic actuation
- steerable guidewire
- ultrasound imaging
ASJC Scopus subject areas
- Control and Systems Engineering
- Biomedical Engineering
- Human-Computer Interaction
- Mechanical Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Control and Optimization
- Artificial Intelligence
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