Optimization of electronic prescription for parallel external fixator based on genetic algorithm

A Computer-Assisted Preoperative Path Planning Method for the Parallel Orthopedic Robot

Background: Trajectory planning is the premise of the control of orthopedic robots, which is directly related to the safety of the human body. However, to date, the trajectory of orthopedic robots has been restricted to lines and spline curves. This limits the flexibility of the robot and leads to unsatisfactory performance. In this paper, a trajectory planning method based on improved RRT* and B-spline curve is proposed in order to improve the control accuracy and flexibility. Method: Firstly, combined with the shortcomings of current trajectory planning methods and bone docking task analysis, the characteristics of the trajectory for orthopedic robot are illustrated, and the problem is described. Secondly, a sampling strategy and an extension strategy are proposed to solve the optimal problem of the RRT* algorithm. Meanwhile, B-spline curve is selected for path smoothing. Thirdly, based on our orthopedic robot, kinematics analysis is introduced briefly, and hypotonic polynomial is used to fit the joint variables. Finally, a comparative study of the improved RRT*, RRT*, and other algorithms are completed, and the feasibility of the robot’s trajectory is verified by algorithm simulation and platform simulation. Results: Compared with RRT*, shorter path and high node utilization are shown in the improved RRT*, which cut down about 1mm in the average path length and increased about half in the average node utilization. In the meantime, the fitting results are accepted, and the results of algorithm simulation and platform simulation showed good consistency and feasibility. Conclusions: This study revealed that the improved RRT* was superior to RRT*, and the proposed method could be used for the trajectory planning of parallel orthopedic robots, which has some significance for bone fracture and deformity correction.

Automatic Femoral Deformity Analysis Based on the Constrained Local Models and Hough Forest

Clinically, Taylor spatial frame (TSF) is usually used to correct femoral deformity. The first step in correction is to analyze skeletal deformities and measure the center of rotation of angulation (CORA). Since the above work needs to be done manually, the doctor's workload is heavy. Therefore, an automatic femoral deformity analysis system was proposed. Firstly, the Hough forest and constrained local models were trained on the femur image set. Then, the position and size of the femur in the X-ray image were detected by the trained Hough forest. Furthermore, the position and size were served as the initial values of the trained constrained local models to fit the femoral contour. Finally, the anatomical axis line of the proximal femur and the anatomical axis line of the distal femur could be drawn according to the fitting results. According to these lines, CORA can be found. Compared with manual measurement by doctors, the average error of the hip joint orientation line was 1.7°, the standard deviation was 1.75, the average error of the anatomic axis line of the proximal femur was 2.9°, and the standard deviation was 3.57. The automatic femoral deformity analysis system meets the accuracy requirements of orthopedics and can significantly reduce the workload of doctors.

Influence of parameter deviation on the closeness of the tibial limb and external fixator based on a novel collision detection algorithm

The Ortho-SUV frame (OSF) is a hexapod external fixator widely applied in orthopedics deformity correction. The possibility of collision between OSF's struts and the soft tissue is an essential but overlooked issue. To avoid the issue, a novel collision detection algorithm is established based on a cone-cylinder model of the tibial limb-strut interaction for detecting the closeness of the tibial limb and external fixator. The algorithm is constructed using the vector analysis based on the model of the minimum distance between the truncated cone generatrix and the cylinder axis. The motion simulation is performed on the overall alignment through the Solidworks-motion module to verify the feasibility of the algorithm. Subsequently, the installation parameter deviations of the bone-fixator system are described to investigate the influence of orientation and position deviation on the closeness of the tibial limb and external fixator through the numerical method. The investigation results show that the orientation deviation γ (around the z-axis), the position deviation τ₁ and τ₂ (along the x and y-axes, respectively) have greater sensitivity to closeness and the influence of multiple deviations on the closeness has the property of superposition. The proposed algorithm can assist clinicians to strictly design and appraise frame configurations prior to their application to avoid the collision between the external fixator and the limbs during the correction. It has great application significance in the development of computer-aided correction software.