In the field of minimally invasive surgery (MIS), practitioners or surgeons use steerable flexible needles for insertion inside the tissue region under treatment, providing an advantage in improving needle positioning accuracy. Challenges arise due to issues such as tissue inhomogeneity, insufficient needle steering strategy, and deformation of needles inside the tissue. The primary goal of percutaneous interventional procedures is to ensure the safety of patients while achieving precise positioning of the needle at a specified target location inside the tissue. Numerous researchers have previously explored diverse approaches to designing proper steering controllers for accurate needle positioning. In response to the complexity associated with existing strategies, this study focuses on implementing a needle steering controller involving a fuzzy inference system. In this work, two distinct fuzzy inference systems are developed to steer a bevel-tip flexible needle within a desired plane. One of the developed fuzzy inference systems involves the Lyapunov analysis-based fuzzy rule base, whereas the other model employs the neural network to build the adaptive rule base depending on previous states. The effectiveness of the designed controllers has been verified through comprehensive simulations while involving comparative analyses with existing controllers in the needle regulation objective domain. In addition to the simulation study, real-time needle interventional experiments involving biological tissue have also been conducted to validate devised needle steering control strategies.
Development of Fuzzy Controller for a Flexible Bevel-Tip Needle in Percutaneous Interventional Procedures
Discovering the Frontiers of Human-Robot Interaction ; Chapter : 9 ; 215-231
2024-07-24
17 pages
Article/Chapter (Book)
Electronic Resource
English
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