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Catheter modelling and force estimation in endovascular application

Li, C. (2023) Catheter modelling and force estimation in endovascular application.

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Abstract:Cardiovascular disease (CVD) is the leading cause of death worldwide. As a minimally invasive treatment, vascular interventional therapy has been widely used in different disciplines such as vascular surgery, cardiovascular surgery, and neurosurgery. Robotic platforms have been designed to assist surgeons, in order to increase accuracy, repeatability, comfort, and post-operatory recovery times. One major limitation of endovascular robotic platforms with respect to the manual approach is the lack of direct contact with the fingers and instruments. The loss of tactile sense will make the operator's hand-eye coordination difficult. Especially in the process of vascular intervention, it is difficult for doctors to estimate the operation force only by imaging e.g., fluoroscopy, which may easily cause blood vessel rupture. In this thesis, inspired by robotic platform for endovascular interventions – CathBot (developed at the Imperial College London), a physical model-based method is proposed to estimate the contact force of the catheter. A catheter model is established based on beam theory, and a 3D vascular model of the abdominal aorta (silicon phantom) is reconstructed from CT data. The contact between the catheter and the phantom model is detected and friction is considered for the simulation of the catheterization process using a simulation framework (SOFA). Experiments are set up to measure the contact force as well as the catheter position during the actual insertion process. The proposed method estimates the contact force on the whole catheter during the insertion process with an average error of 0.04N with respect to the experiment results. The position of the catheter tip obtained by simulation is within the acceptable error range (average error 3.1mm with respect to the experiment results), and the configuration of the whole catheter can be obtained.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:52 mechanical engineering, 53 electrotechnology, 54 computer science
Programme:Electrical Engineering MSc (60353)
Link to this item:https://purl.utwente.nl/essays/94002
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