Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces

Buschbaum, Jan; Fremd, Rainer; Pohlemann, Tim; Kristen, A.

doi:10.1007/s11548-017-1562-0

Cited by 18 publications

(19 citation statements)

References 26 publications

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“…If the distance |ΔX| between the current pose and the target pose of the distal segment is larger than |V vf |·ΔT, the guiding speed is regulated to maintain a predetermined constant speed |V vf |, as shown in Equation 10. If |ΔX| is less than |V vf |·ΔT, the robot's pose is updated to the target pose, as shown in Equation 11. In addition, to allow the surgeon to modify the path of the robot, V h ·ΔT is added.…”

Section: Linear Guidance Constraints For Fracture Reduction Surgerymentioning

confidence: 99%

“…Buschbaum et al developed an automatic fracture reduction algorithm using a path planner based on an A* algorithm and a surface correlation algorithm using their 3D model to identify the relative pose between the bone fragments. 11 As indicated above, various path planner-based automatic fracture reduction algorithms have been developed. However, most of them have been either limited to simple fracture cases, 4,8 or it has not been easy for surgeons to intervene in the robot's motion while it was moving.…”

Section: Introductionmentioning

confidence: 99%

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Hands‐on robot‐assisted fracture reduction system guided by a linear guidance constraints controller using a pre‐operatively planned goal pose

Kim

2018

Robotics Computer Surgery

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Background:In robot-assisted fracture reduction systems, the fine alignment of the fractured bone and its path planning are still of issues that need to be resolved. Methods:A novel linear guidance constraints (LGC) controller guides a robot along the shortest path to align a distal fracture segment and a proximal one. In addition, the surgeon can modify the path whenever s/he wants. Results:When the LGC controller is used in the experiment on a femoral bone model with simulated muscles, the fracture reduction time was measured to be 35.6 ± 16.4 seconds, while the position and the angle errors were 0.41 ± 0.61 mm, and 0.22 ± 0.80°, respectively. The proposed controller reduced the reduction time by 78.1%, the translational error by 91.6%, and the angular error by 95.4%, compared with the cases without the LGC controller. Conclusions:It was proven that the proposed scheme reduced the reduction time and the pose error of the fracture alignment, and that it is effective to alleviate the maneuvering load.

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Section: Linear Guidance Constraints For Fracture Reduction Surgerymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hands‐on robot‐assisted fracture reduction system guided by a linear guidance constraints controller using a pre‐operatively planned goal pose

Kim

2018

Robotics Computer Surgery

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“…With the development of robot technology and computer‐assisted navigation technology, robot‐assisted surgeons can complete high‐precision surgical operations 1–12 …”

Section: Introductionmentioning

confidence: 99%

“…orientation was pre-adjusted, and the path planning process only considered the displacement deviation of the distal fragment relative to the proximal fragment. 7 In 2019, Zhu et al proposed a robotassisted fracture reduction method based on vision. Real-time imaging of the fracture model was performed using a G-arm X-ray machine to obtain anteroposterior and lateral views of the proximal fragment and the distal fragment, using two spatial out of plane lines representing the proximal fragment and the distal fragment, and the motion of the distal fragment was controlled manually through a 6-DOF parallel robotic platform to gradually reduce the angle between the proximal fragment and the distal fragment in two views to achieve the reduction effect.…”

mentioning

confidence: 99%

Constraint of musculoskeletal tissue and path planning of robot‐assisted fracture reduction with collision avoidance

Lei

et al. 2022

Robotics Computer Surgery

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Background: For the robot-assisted fracture reduction, due to the complex fracture musculoskeletal environment, it is necessary to consider the influence of soft tissue traction on preoperative reduction path planning.Method: An improved 3D A* algorithm is adopted to plan the fracture reduction path. The distal fragment point clouds are updated to avoid the collision, and the end point coordinates of the muscles are updated to calculate muscular lengths during the path search.Results: 3D reduction path of long-bone fracture is planned, effectively avoiding the fracture fragments collision and ensuring the length of the corresponding muscle is always less than the allowable maximum muscle length after elongation. Conclusion:The proposed method can effectively avoid the collision between the distal fragment and the proximal fragment during the fracture reduction, can avoid secondary injury of the muscles around the femoral bone caused by overdistraction, and effectively improve the safety of robot reduction operation.

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“…Du et al 47 defined a new fracture classification and took the type of fracture fragments into account in preoperative trajectory planning. Buschbaum et al 48 investigated the influence of the muscle force on the reduction mechanism during reduction. From the current research, the detailed kinematics and mathematical derivation of the collision detection algorithm have not been published, which is very complicated calculation progress and is imperative for trajectory planning and preoperative evaluation.…”

Section: Introductionmentioning

confidence: 99%

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

Zuo

et al. 2021

Numer Methods Biomed Eng

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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.

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Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces

Abstract: A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.

Cited by 18 publications

References 26 publications

Hands‐on robot‐assisted fracture reduction system guided by a linear guidance constraints controller using a pre‐operatively planned goal pose

Hands‐on robot‐assisted fracture reduction system guided by a linear guidance constraints controller using a pre‐operatively planned goal pose

Constraint of musculoskeletal tissue and path planning of robot‐assisted fracture reduction with collision avoidance

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

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