A Surgical Robotic System for Long-Bone Fracture Alignment: Prototyping and Cadaver Study

Saeedi-Hosseiny, Marzieh S.; Alruwaili, Fayez; McMillan, Sean; Iordachita, Iulian; Abedinnasab, Mohammad H.

doi:10.1109/tmrb.2021.3129277

Cited by 13 publications

(12 citation statements)

References 56 publications

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“…The measurement system provides surgeons with real-time information, which can help doctors to reduction fractures within the safe range of applied force and torque. A new robotic system for long-bone reduction was developed by Mohammad H. et al [12]- [14], who designed a new six-degree-offreedom open-loop resetting robotic system for long-bone fracture reduction. By means of simulation analysis, it was concluded that the robot could carry a load force of 50 kg, and test experiments on cadavers were conducted to demonstrate the high precision and large load capacity performance of the robot.…”

Section: Introductionmentioning

confidence: 99%

Configuration design and load capacity analysis of pelvic fracture reduction robot

Cai¹,

Lei²,

Rao³

2023

J. vibroeng.

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Robot-assisted reduction of pelvic fracture requires large workspace and large load capacity. A kind of six degree-of-freedom (DOF) robot for pelvic fracture reduction is designed, which is a hybrid configuration composed of three-revolute-revolute-revolute (3RRR) parallel mechanism and three-dimensional guide rail. The hybrid configuration can ensure that the robot meet the needs of large workspace and large load capacity. Through the comparative analysis of dynamic and virtual prototype simulation, the reduction force of the designed reduction robot can reach 200 N. The experimental results show that the robot not only has the characteristics of high precision and high load of parallel robot, but also has the characteristics of large workspace of series robot.

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Section: Introductionmentioning

confidence: 99%

Configuration design and load capacity analysis of pelvic fracture reduction robot

Cai¹,

Lei²,

Rao³

2023

J. vibroeng.

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show abstract

“…Then, the planned reduction path is transmitted to the robot, and the robot performs fracture reduction autonomously 2–4 . Another way of fracture reduction without collision is to manually manipulate the fracture reduction robot to control the distal fragment for position and orientation adjustment 5,6,8,10 . In 2015, Du et al 6 .…”

Section: Introductionmentioning

confidence: 99%

“…The system can provide larger traction forces, torques and rotational workspace. The performance verification was performed by the cadaver test guided by intraoperative X‐ray imaging 10,11 …”

Section: Introductionmentioning

confidence: 99%

“…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%

“…The performance verification was performed by the cadaver test guided by intraoperative X-ray imaging. 10,11 In this paper, the reduction path of femur fracture is planned. In order to improve the precision and safety of robot-assisted fracture reduction surgery, an improved 3D A* searching method is proposed, which mainly considers the collision avoidance between the distal fragment and proximal fragment.…”

mentioning

confidence: 99%

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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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Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network

Lei,

Wang

2024

Robotics Computer Surgery

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BackgroundFor the fracture reduction robot, the position tracking accuracy and compliance are affected by dynamic loads from muscle stretching, uncertainties in robot dynamics models, and various internal and external disturbances.MethodsA control method that integrates a Radial Basis Function Neural Network (RBFNN) with Nonlinear Disturbance Observer is proposed to enhance position tracking accuracy. Additionally, an admittance control is employed for force tracking to enhance the robot's compliance, thereby improving the safety.ResultsExperiments are conducted on a long bone fracture model with simulated muscle forces and the results demonstrate that the position tracking error is less than ±0.2 mm, the angular displacement error is less than ±0.3°, and the maximum force tracking error is 26.28 N. This result can meet surgery requirements.ConclusionsThe control method shows promising outcomes in enhancing the safety and accuracy of long bone fracture reduction with robotic assistance.

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A Surgical Robotic System for Long-Bone Fracture Alignment: Prototyping and Cadaver Study

Cited by 13 publications

References 56 publications

Configuration design and load capacity analysis of pelvic fracture reduction robot

Configuration design and load capacity analysis of pelvic fracture reduction robot

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

Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network

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