Investigation of Guidewire Deformation in Blood Vessels Based on an SQP Algorithm

Abstract

This paper proposes a solution to the simulated deformation of guidewires when they come in contact with the blood vessel in an interventional surgery simulation training system. Starting from the principle of minimum energy, the guidewire is evenly dispersed into a rigid light bar articulation model. A sequential quadratic programming (SQP) algorithm is used to nonlinearly optimize the deflection angle of each light bar. When the elastic potential energy of the guidewire reaches a minimum, we can get the guidewire deformation we want to solve. The method proposed in this paper avoids necessity of delving into contact deformation caused by the contact force between the guidewire and the blood vessel wall, while solving the problem of the deformation of the guidewire due to the pose of the contact points. We use an ABAQUS (finite element software) simulation to verify that this solution has a theoretical simulation accuracy of 5.11%, and the designed experiments prove that the actual simulation accuracy is about 11%. Moreover, we also simulated the bending stress state of the guidewire by using the deflection angle of each bar. In addition, in order to achieve the most suitable simulation results, we discuss the discrete density of the guidewire model from the perspective of algorithm time consumption and simulation accuracy.

Design of Mayer Wavelet Neural Networks for Solving Functional Nonlinear Singular Differential Equation

“…Sequential quadratic programming belongs to the class of convex optimization problem-solving technique exploit for both constrained and unconstrained optimization tasks. Few recent submissions of SQP are multiproduct economic production [35], economic load dispatch problems [36], bipedal dynamic walking robot [37], temporary hydrothermal organization [38], analysis of guidewire distortion in the vessels of blood [39], convex quadratic bi-level programming problems [40], Lane--Emden pantograph systems [41], simple LNG process [42], optimal power flow problems [43], and flight recovery for transference aircraft [44].…”

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

“…SQP is executed in numerous optimisation models of numerous complexes as well as non-stiff systems. Presently, it is used to investigate the guidewire deformation in blood vessels [42], in the power system stabiliser design [43], optimal control of rapid cooperative rendezvous [44], 3D deformable prostate model pose estimation in minimally invasive surgery [45], deterministic constrained production optimisation of hydrocarbon reservoirs [46], prediction differential system [47] and in the optimisation of an auxetic jounce bumper [48]. To switch the sluggishness of GA, hybridisation of the GA-SQP process is implemented along with the necessary steps, as provided in Table 1.…”