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. The biggest difference between the surgical robot system and traditional surgery is the lack of direct contact with the fingers. 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, which may easily cause blood vessel rupture.
In this thesis, based on robotic platform for endovascular interventions – CathBot (developed at the Imperial College London), a physical model-based method is proposed to estimate the feedback force of the catheter. A catheter model is established based on beam theory, and the phantom 3D model is reconstructed from the results of MRI and CT scans, and the contact between the catheter and the phantom model is detected and friction is considered for the simulation of the catheterization process using in SOFA-framework. The proposed method accurately estimates the movement of the catheter and the force on the catheter during the insertion process.
