A Hyperelastic Finite-Element Model of Human Skin for Interactive Real-Time Surgical Simulation

OBJECTIVE The underlying biomechanical differences between the pediatric and adult cervical spine are incompletely understood. Computational spine modeling can address that knowledge gap. Using a computational method known as finite element modeling, the authors describe the creation and evaluation of a complete pediatric cervical spine model. METHODS Using a thin-slice CT scan of the cervical spine from a 5-year-old boy, a 3D model was created for finite element analysis. The material properties and boundary and loading conditions were created and model analysis performed using open-source software. Because the precise material properties of the pediatric cervical spine are not known, a published parametric approach of scaling adult properties by 50%, 25%, and 10% was used. Each scaled finite element model (FEM) underwent two types of simulations for pediatric cadaver testing (axial tension and cardinal ranges of motion [ROMs]) to assess axial stiffness, ROM, and facet joint force (FJF). The authors evaluated the axial stiffness and flexion-extension ROM predicted by the model using previously published experimental measurements obtained from pediatric cadaveric tissues. RESULTS In the axial tension simulation, the model with 50% adult ligamentous and annulus material properties predicted an axial stiffness of 49 N/mm, which corresponded with previously published data from similarly aged cadavers (46.1 ± 9.6 N/mm). In the flexion-extension simulation, the same 50% model predicted an ROM that was within the range of the similarly aged cohort of cadavers. The subaxial FJFs predicted by the model in extension, lateral bending, and axial rotation were in the range of 1–4 N and, as expected, tended to increase as the ligament and disc material properties decreased. CONCLUSIONS A pediatric cervical spine FEM was created that accurately predicts axial tension and flexion-extension ROM when ligamentous and annulus material properties are reduced to 50% of published adult properties. This model shows promise for use in surgical simulation procedures and as a normal comparison for disease-specific FEMs.

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A Vision-Based Approach for Estimating Contact Forces: Applications to Robot-Assisted Surgery

Applied Bionics and Biomechanics ◽

10.1155/2005/436897 ◽

2005 ◽

Vol 2 (1) ◽

pp. 53-60 ◽

Cited By ~ 2

Author(s):

C. W. Kennedy ◽

J. P. Desai

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Real Time ◽

Force Feedback ◽

Element Model ◽

Robot Arm ◽

Robot Assisted ◽

Interaction Forces ◽

Fem Model ◽

Nodal Displacements

The primary goal of this paper is to provide force feedback to the user using vision-based techniques. The approach presented in this paper can be used to provide force feedback to the surgeon for robot-assisted procedures. As proof of concept, we have developed a linear elastic finite element model (FEM) of a rubber membrane whereby the nodal displacements of the membrane points are measured using vision. These nodal displacements are the input into our finite element model. In the first experiment, we track the deformation of the membrane in real-time through stereovision and compare it with the actual deformation computed through forward kinematics of the robot arm. On the basis of accurate deformation estimation through vision, we test the physical model of a membrane developed through finite element techniques. The FEM model accurately reflects the interaction forces on the user console when the interaction forces of the robot arm with the membrane are compared with those experienced by the surgeon on the console through the force feedback device. In the second experiment, the PHANToM haptic interface device is used to control the Mitsubishi PA-10 robot arm and interact with the membrane in real-time. Image data obtained through vision of the deformation of the membrane is used as the displacement input for the FEM model to compute the local interaction forces which are then displayed on the user console for providing force feedback and hence closing the loop.

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Real-Time Simulation Analysis of a Floating Dock Based on a Finite Element Model

Proceedings of the Eighth International Conference on Computational Structures Technology ◽

10.4203/ccp.83.219 ◽

2009 ◽

Author(s):

Y.D. Liu ◽

Ch.M. Sun ◽

G. Bian

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Real Time ◽

Simulation Analysis ◽

Element Model ◽

Real Time Simulation ◽

Time Simulation

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Methods for Reducing a Thermal Finite Element Model Including the Advection Network Contribution

Volume 3: Heat Transfer, Parts A and B ◽

10.1115/gt2006-90676 ◽

2006 ◽

Author(s):

Daniele Botto ◽

Stefano Zucca ◽

Muzio M. Gola

Keyword(s):

Finite Element ◽

Finite Element Model ◽

Real Time ◽

Residual Life ◽

Mathematical Formulation ◽

Time Integration ◽

Element Model ◽

Computational Time ◽

Fatigue Damage Accumulation ◽

Secondary Air

The life monitoring concept needs on-line calculation to evaluate stresses and temperatures on aircraft engine components, in order to asses fatigue damage accumulation and residual life. Due to the amount of computational time required it is not possible for a full finite element model to operate in real time using the on-board CPU. Stresses and temperatures are then evaluated by using simplified algorithms. In the present work Guyan reduction and component mode synthesis have been applied to a thermal finite element model, including the cooling stream flow — the so called advection network — in order to reduce the size of the solving equation system. The appropriate mathematical formulation for the advection network reduction has been developed. Two reduction methods have been performed, discussed and subsequently applied to a thermal finite element model of a real low pressure turbine disk. The reduced system includes both the disk and the correlated fluid network model, simulating turbine secondary air system. The finite element model is axi-symmetric, with constant convective coefficients. Results of time integration for the reduced and the complete models have been compared. Results show that the proposed techniques gives models with a reduced number of degrees of freedom and at the same time good accuracy in temperature calculation. The reduced models are then suitable for real time computation.

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Dynamic Path Planning for Bevel-Tip Flexible Needle Insertion into Soft Tissue Based on a Real-Time Finite Element Model

Mathematical Problems in Engineering ◽

10.1155/2020/4512409 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Murong Li ◽

Dedong Gao ◽

Yong Lei ◽

Tian Xu

Keyword(s):

Finite Element ◽

Soft Tissue ◽

Path Planning ◽

Finite Element Model ◽

Real Time ◽

Ccd Camera ◽

Element Model ◽

Online Planning ◽

Dynamic Path Planning ◽

Dynamic Path

This paper presents a novel dynamic path planning methodology for needle steering into the soft tissue. A real-time finite element model is used to simulate the procedure of a flexible needle into the homogeneous soft tissue, which provides the dynamic deformation information for the path planning. The relationship between needle base and tip is formulated as the transformations of homogeneous matrix with quasi-static assumptions. Based on the reachability of the flexible needle, the real-time motions of obstacles and target are considered through the dynamic needle-tissue interactions. A testbed including a XY linear stage, one rotator, and a CCD camera is constructed, and the experiments are designed to validate the proposed method. The 23G PTC needle was inserted into the PVA phantom with markers, and the CCD camera was utilized to record the needle trajectories and motions of target and obstacles. The targeting errors between the experimental and planned paths are less than 1.20 mm, and the distance from the obstacle to needle is not smaller than 1.16 mm. The results demonstrate that the proposed algorithm is effective for online planning the paths in the needle-tissue interactive environment.

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A Real-Time Neural Network Estimator for Workpiece Thermal Expansion Errors

10.1115/imece2000-1472 ◽

2000 ◽

Author(s):

A. D. Yoder ◽

R. N. Smith

Keyword(s):

Neural Network ◽

Finite Element ◽

Thermal Expansion ◽

Finite Element Model ◽

Real Time ◽

Element Model ◽

Precision Machining ◽

Machining Processes ◽

The Neural Network ◽

The Finite Element Model

Abstract The importance of predicting and reducing thermal expansion errors in workpieces is becoming greater as better precision machining processes are developed. An artificial neural network model to estimate the workpiece thermal expansion errors in real-time during precision machining operations is developed and compared with experimental results. A finite element model of workpiece thermal expansion has been created to predict expansions in a thin cylinder undergoing a turning process. The neural network has been trained using finite element model solutions over a range of conditions to allow for changing machining parameters. To realize “on-line” capability, the measurable values of heat flux into the workpiece, surface heat transfer coefficient, and tool location are used as inputs and the expansion as the output for the neural network. The estimations of the network are compared with experimental results from a turning process on a large diameter aluminum cylinder. There is reasonable agreement between measured and estimated expansions with an average error of 18%. The neural network has not been trained at the cutting conditions used during the experiment. The speed of the neural network estimation is much greater than the solution to the finite element model. The finite element model required over 15 minutes to solve on a Pentium 133Mhz computer. The neural network calculated the expansions easily at 1 Hz during the experiment on the same computer. With real-time estimation using measurable data, compensation can be made in the tool path to correct for these errors. The application of this method to precision machining processes has the capability of greatly reducing the error caused by workpiece thermal expansions.

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