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motion. It showed new insight of the intrinsic dynamic hidden by uncertainties propagation. Our method is subject to limitations. Firstly, parametric optimization can be currently only implemented for smooth dynamic movements. As a result, high impact motions are not handling by this method. Secondly, the criterion does not consider force plate uncertainties. Kuo (1998) and Cahoüet et al. (2002) injected these parameters within the least-square optimization. Such an approach could be also carried out by addition of a weighting matrix with the criterion. However, the influence of these uncertainties may be negligible because force plate manufacturers proposed high accurate sensors currently. Thirdly, joint torques were adjusted while keeping a classical anthropometric model. Results obtained using our dynamic optimization approach may be improved by integrating a preliminary numerical process. Inertial parameters could be personalized by means of optimization or identification methods published recently by Riemer et al. (2008) and Monnet et al. (2008), respectively. In conclusion, the acceleration adjustment method improves the dynamic model by proposing input kinematic data in accordance with force measurement. This innovative method allowed computing joint accelerations without implement the double differentiation. Improving joint torque computation should lead to better analyze human movement coordination perform during complex tasks. 6. REFERENCES 1. Riemer R., Hsiao-Wecksler E. and Zhang X., Uncertainties in inverse dynamics solutions: a comprehensive analysis and an application to gait, Gait Posture, 2008,Vol. 27, 578-88 2. Delp S., Anderson F., Arnold A., Loan P., Habib A., John C. and Guendelman, E., OpenSim: open-source software to create and analyze dynamic simulations of movement, IEEE Trans. Biomed. Eng., 2007, Vol. 54(11), 1940-50. 3. Riemer R. and Hsiao-Wecksler E., Improving net joint torque calculations through a two-step optimization method for estimating body segment parameters, J. Biomech. Eng., 2009, Vol. 131(1). 4. Ehrig R., Taylor W., Duda G., and Heller M., A survey of formal methods for determining the centre of rotation of ball joints, J. Biomech., 2006, Vol. 39(15), 2798-809. 5. Blajer W. and Czaplicki A., Modeling and inverse simulation of somersaults on the trampoline, Journal of biomechanics, 2001, Vol. 34(12), 1619-29. 6. Kuo A., A least-squares estimation approach to improving the precision of inverse dynamics computations, J. Biomech. Eng., 1998, Vol. 120, 148-59. 7. Cahouët V., Martin L. and Amarantini D., Static optimal estimation of joint accelerations for inverse dynamics problem solution, J. Biomech., 2002, Vol. 35(11), 1507-13. 8. Luh J., Walker M. and Paul R., On-line Computaional sheme for mechanical manipulators, J. Dyn. Syst.-T. ASME, 1980, Vol.102, 69-76. 9. de Leva P., Adjustments to Zatsiorsky-Seluyanov’s segment inertia parameters, J. Biomech., 1996, Vol. 29(9), 1223-30. 10. Monnet T., Atchonouglo E., Vallée C. and Fortuné D, Identification of the ten inertia parameters of a rigid body, J. Appl. Math. Mech., 2008, Vol. 72, 22-25.
NEURAL NETWORK-BASED PREDICTION OF HAND POSTURES FOR GRASPING SIMULATION WITH A BIOMECHANICAL MODEL M.C. Mora 1 , J.L. Sancho-Bru 2 , J.L. Iserte-Vilar 1 and A. Pérez-González 3 1. ABSTRACT Most human interactions with the environment are performed by the hands. This versatility is due to their more than 20 degrees of freedom. A lot of research has been done in the field of robotic grasping in the last years [1,2]. All this work can be extended to the biomechanics field due to the similarity between the grasping problem in robotic and human hands, considering that the former are kinematically simpler than the latter. In [3] we proposed a hand biomechanical model that merged the current knowledge on biomechanics, ergonomics and robotics. One of the aims of this proposal was to predict feasible grasping postures for a given object. As a first approach, we present here a methodology for automatically generating grasping postures by means of artificial neural networks (ANNs), inspired by the works presented in [1] and [4]. The inputs to the ANN are the characteristic hand data, the dimensions of the object to be grasped and the task. The outputs are the joint angles of the hand. For the training, validation and test stages, we use data measured from a Cyberglove device. Our goal is to estimate the hand posture performed when grasping objects of the daily life. 2. INTRODUCTION The study of the human grasp is very interesting because of the knowledge it can provide regarding manipulation [5]. In the last two decades a lot of research has been carried out in the field of robotic grasping [1, 2, 5, 7] and is currently a very hot topic. Many of the existing techniques could be extended to the biomechanics’ field due to the similarities between human and robotic hands, although the former are simpler that the latter. Within the wide variety of grasp-related problems, the computation of grasping postures associated to particular objects is one of the most challenging, as it implies the fulfillment of a large number of constraints that relate not only to the hand structure and to the object, but to the requirements of the environment and the task to be performed. From the biomechanics’ viewpoint, there are different studies of the grasping process but very few tackle the prediction of grasping postures for given objects and tasks. Hand posture prediction is an important issue as it allows the evaluation of biomechanical and ergonomic parameters related to grasping [7, 8]. However, the few related works usually measure hand postures using specific devices, such as data gloves [9], instead of 1 Assistant Professor, Mechanical Engineering and Construction Department, Universitat Jaume I, Avda. Vicent sos Baynat, 12071, Castellón, Spain 2 Associate Professor, Mechanical Engineering and Construction Department, Universitat Jaume I, Avda. Vicent sos Baynat, 12071, Castellón, Spain 3 Professor, Head of the Mechanical Engineering and Construction Department, Universitat Jaume I, Avda. Vicent sos Baynat, 12071, Castellón, Spain
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The Proceedings of the 10 th Intern
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Install Adobe Reader 8 or 9 (http:/
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Content: POSTERS: BRAIN: CELL: EVAL
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Modeling of blood flow through a fl
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The mesh generation of the model wa
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Figure6 . The stroke volume data fo
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Digital Subtraction Phonocardiograp
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mobile cart for easy recording in c
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Figure 7. This image shows PCG samp
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Our approach is an improvement in t
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one cements as well as its behaviou
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Typical dimensions of lumbar verteb
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attributed to the change of stiffne
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lifestyle and obesity. In that cont
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T was the temperature in Kelvin and
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sustained tensile strains stimulate
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An approach aiming at determining a
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failure load. 2.4 Simulation of reh
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REFERENCES 1. Vunjak-Novakovic G, A
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3. FIF-BAL BIOREACTOR The FIF devic
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value of p nearest to dqc=0 we cont
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(Wanless, 1999). This low value cou
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3. MATERIALS AND METHODS A CAD mode
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did not allow gap closure. Maximum
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hand, if the IFM is too large, remo
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2. INTRODUCTION Intervertebral disc
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Figure 3. T1 signal enhancement in
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1. ABSTRACT TIP CELLS AT THE TOP: M
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Fig. 1. Schematic overview of the m
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Fig. 3. Image of the amount of VEGF
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THE COMPUTATIONAL MODEL OF DENTAL I
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processing application STL Model Cr
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For the implant/bone interaction as
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ABSTRACT THE IMPACT OF SELECTION BI
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Figure 1: flow chart showing the op
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Figure 2: Time course of cytosolic
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CONSTITUTIVE MODELLING OF THE ANNUL
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it is well known the non-linear nat
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Therefore, we have decided to carry
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EXTRACTION OF PHALANGEAL JOINT PARA
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column vectors of P. Denoting the v
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End i joint angles and length offse
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Validation of Strain Mapping for th
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allows the calculation of strain ma
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RMS error was 0.054 and the strains
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AN APPROACH FOR THE REDUCTION OF TH
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The relation between the time-deriv
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Error in position [mm] Error in pos
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ANALYSIS OF THE INTRAINDIVIDUAL DIF
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Fig.1: Frontal view on all subchond
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[6] M. Bozkurt, B. B. Kentel, G. Ya
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on the actual necessary time needed
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Illustration 2: The initially spher
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cell if it is hardly able to deform
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fit with a reference anatomy in min
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show that patellar mal-positioning
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Experimental and numerical analysis
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stenosis in both simulations and ex
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stented case, corresponding to the
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EVALUATION OF DIFFERENT LOADING CON
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were modeled with identical geometr
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each simulation and the position of
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FINITE ELEMENT MODEL ANALYSIS OF HU
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Figure 1: Maximal principal strains
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Method for classification of porcin
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3.3 Identification of Paths Accordi
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Table. 1. Descriptive Patterns used
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CHARACTERIZING THE MECHANICAL MICRO
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3.1.3 Cell proliferation It is assu
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Stress [Pa] 4 3 2 1 0 Mean stress A
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REFERENCES [1] A.M. Bratt-Leal, R.L
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y exposure to interstitial fluid sh
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according to (Eq. 2), nor averaged
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emoved the oscillations partially a
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static load and a dynamic load. A s
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positive effect of the number of ac
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pathways and their interactions tha
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applications, the need for accuracy
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avoid violating the initial geometr
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6. CONCLUSION The examples of appli
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Fig. 1 Semicircular canal structure
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4. RESULT Fig. 6 FSI model of semic
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6. ACKNOWLEDGEMENT This research wa
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ods to the biocompatible plastic po
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Table 1: Analysis conditions Static
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[3] Brantigan, J. W., Steffee, A. D
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femoral head fracture, the femoral
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Fig 3. Schematic drawing of the ste
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6. CONCLUSION Fig 7. Analysis resul
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and angular rates were registered b
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former, there were assumed the foll
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delivered dynamic support, which pr
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insertion of provisional restoratio
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Figure 4: Implant displacements obt
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5. DISCUSSION AND CONCLUSION Initia
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at which microdamage originates. Fo
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4. RESULTS The load response varied
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current study to explore the effect
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implant correctly from the finite e
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(a) (b) (c) (d) (e) Figure 3. The s
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(a) (b) Figure 6. The meshed model
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(a) (b) Figure 9. Cumulative probab
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NUMERICAL EVALUATION AND MEDICAL CO
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compared by overlaying the real dat
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four sample patient data, outcomes
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A POROELASTIC APPROACH FOR AN OPEN
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where indexes U, P refer to the unk
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RESULTS As a preliminary test, a 0.
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BIOMECHANICAL BEHAVIOR OF CANCELLOU
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cement acts perfectly, therefore it
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cancellous bone of natural joints a
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COMPUTATIONAL MODELING OF TANGLED A
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The centers of the simulated cells
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untangled, the local fiber displace
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TOWARDS A WAVELET BASED MEDICAL IMA
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however at each decomposition scale
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the MATLAB software (for the Modifi
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A FLUID STRUCTURE INTERACTION MODEL
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hyperelastic based on available exp
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t [ms] 30 70 160 220 270 Pressure [
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MECHANICAL BAHAVIOR OF DIFFERENT NI
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parameters necessaries to use this
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F1 and Mtwo were directly related t
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MECHANICAL EFFECT ON METABOLIC TRAN
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an initial nil lactate concentratio
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present study, such values were phe
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EVALUATION OF FEMORAL COMPONENT MIC
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TS implants employed a “hybrid”
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5. DISCUSSION i ii Figure 2: Compar
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THE MECHANICAL ENVIRONMENT IN THE D
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instead the femur was supported by
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It must be noted however, that in t
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1. ABSTRACT MODELING OF ARTICULAR C
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exp 1 1 2 1 where and are i
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Implant Fig.2. Axisymmetric represe
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A MULTI-SCALE ANISOTROPIC CONSTITUT
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3.2 Decoupled invariant formulation
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Fig. 1. Experimental data from unia
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VALIDATION AND CALIBRATION PROCESSE
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Figure 1: A three-step process simu
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The validation process employed on
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FLUID-STRUCTURE INTERACTION ANALYSI
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The coupled SQA model and the conve
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Point P7, located at the toe of the
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THE INFLUENCE OF UNCERTAIN ANATOMIC
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Figure 3 exemplifies for intradisca
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8. CONCLUSIONS Unsurprisingly, the
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COMPARISON OF DIFFERENT LOADING CON
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Figure 1 Finite element model of th
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6 CONCLUSION It is a feasible way t
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FROM CELL CONTRACTILITY TO CURVATUR
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4. MODEL When cells adhere on a sub
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organisation. Understanding the pri
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PREOPERATIVE PLANNING SUPPORT SYSTE
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[9]. Stenosis of 25, 45, 65 and 85
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Fig. 1:Dependent and independent va
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1. ABSTRACT Local strain measuremen
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around 100µm (halfway through the
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sampling points at different cross
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CLASSIFICATION OF PHYSICAL ACTIVITY
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induces a vertical alignment of the
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accelerations combination). However
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line under translation. Information
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In this study, we apply a meshless
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used the PAC constitutive constants
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1006031) is gratefully acknowledged
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improvements were seen in both grou
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Pre-augmentation Position 1, V=3mL
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5. ACKNOWLEDGEMENTS Funding for thi
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the hemodynamics in cerebral aneury
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4. RESULTS AND DISCUSSION In order
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processing methods need to be devel
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3. METHODS 3.1 Experimental Method
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Figure 2 - Micrographs for tensile
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analysis of the tissue mechanics. B
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3. METHODS 3.1 Specimen Preparation
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of five points across the mid mid-c
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equired to replicate the deformatio
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pre-load within the plate (compress
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4. RESULTS The load-deformation beh
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fracture fixation. Medical Engineer
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model. It approximates knee kinemat
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computational cost remains moderate
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Concerning the optimization procedu
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aesthetic recovery. However, in som
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atio experimented by both wounds is
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VARIATION OF MICRO-ARCHITECTURE AND
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osteoporotic (OP). The sample volum
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Figure 4: Mean error in orthotropy
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INVESTIGATION OF CORTICAL SHELL STR
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When creating the degenerated FE mo
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Figure 4. Degeneration sensitivity
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METHODS TO ACCELERATE FINITE ELEMEN
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the “joint” constraints configu
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Figure 4: Absolute prediction error
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EFFECT OF POST TREATMENT FOR MULTIP
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Fig.2 Inlet velocity profile indica
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4.3 WSS results Figure 8 shows the
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approximated by the so-called Ritz
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Figure 2: Viscohyperelastic cube: (
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There is no optimal density-elastic
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Fig. 2 Cut view of FE-model. Shown
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5. Weis JA, Miga MI, Granero-Moltó
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3. SYSTEM DESIGN Sheep eyes, as the
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which provides natural tactile feed
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113:341-342 20. Henderson B. A., Gr
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health area. According to estimates
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Table 1. RMS Value based on subject
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6. REFERENCES 1. http://www.disable
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ehavior [5]. From the viewpoint of
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Fig. 1 Average Male and Female's L4
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4. Deyo, R.A., and Weinstein, J. N.
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geometry of the cell and ECM degrad
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Shown in Fig. 2(b) is a plot of the
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6. REFERENCES 1. Dubin-Thaler B.J.,
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We implemented our individual-based
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3.3.1 Centers of mass Table 1: Base
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average coordination num ber averag
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BIOMECHANICAL ANALYSIS OF THE MUSCU
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of the ligament strain; a linear re
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lengthening, respectively, if compa
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THE EFFECT OF HIGH TIBIAL OSTEOTOMY
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The 3D LiveWire tool was used as an
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Table II: Peak medial and lateral f
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INVESTIGATING CHANGES IN JOINT LOAD
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4. RESULTS Table 1 shows the mean m
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Fig.5 displays the OKS and KOS pre
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Dynamic Touch of Effective Golf Swi
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properties of a golf club and hand
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perturbation in e3 whereas player B
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1. Kim, W., Response to letter to t
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configuration.[4] have explained ho
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compartments as well as a single mu
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5. Shabana, A.A., Dynamics of multi
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Five healthy volunteers (age: 38.3
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internal lumbar spinal shape was de
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Airflow Simulation of Nasal Cavity
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temperature [5], and Wbl is the wat
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Figure 8. Figure 8(a) illustrates t
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Finite element models of the hip ca
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3.2 Finite Element Analysis Followi
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5. DISCUSSION Previous DEA implemen
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STATISTICAL SHAPE MODELING OF CAM-T
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Thirty-three control femurs (25 mal
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asymptomatic subjects 7,9 . The Hot
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6. REFERENCES 1. Ganz, R., Parvizi,
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NUMERICAL IDENTIFICATION OF THE PER
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2. METHOD AND NUMERICAL MODEL. 2.1
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1 u dV V u. (Eq. 2) V The permeab
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1. ABSTRACT PASSIVE AND ACTIVE MUSC
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presented in figure 2 the simulatio
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Indenter Stroke [mm] Muscle Force [
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Objectives Long bone failure charac
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the specimens in three point bendin
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developing a subject-specific finit
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Models used in the past, mostly bas
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In this work it is presented the de
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Average Table 1.- Walk average test
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angles for the step of 2.28° and 8
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insufficiency syndrome (TIS), defin
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a) b) c) Fig. 5 - Contact interface
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EOS. Among these options, VEPTR has
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dissection occurs when blood intrud
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mean value of 0.0310 m s -1 . The o
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progression. It can in turn contrib
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dependent data. They conclude that
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found that it is extremely difficul
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endering loop is started and the ra
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3.1 Imaging protocol of the knee A
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Fig. 3: Pressure distribution in th
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7. REFERENCES 1. Masouros, S.D., Bu
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and estimate in vivo tissue strains
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tendon has a larger moment arm abou
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Song, H. M., Smith, R. L., Longaker
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Fig. 1. Single line transducer resu
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Let P INT be the data set of the lo
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could quantify the initial structur
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expansion of a stent, a metallic sc
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immediately after stent expansion a
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6. ACKNOWLEDGMENT This research is
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Deformation of the arterial surface
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separate study to be described in a
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3. Timmins, L.H., Miller M.W. Clubb
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migrate in a unique fashion to the
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Fig. 1: Domain and schematic repres
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Furthermore, the values are spread
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this study, our goal is to establis
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Figure 3. Relative length change in
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5. Erdemir A, Sibole S. Open Knee:
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lateralis (inferior and superior) f
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during mouth closing and chewing. O
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BIOMECHANICAL MODELING OF THE HUMAN
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appropriates mechanical properties
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Fig. 4: Correlation of the location
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1. ABSTRACT COMPUTER AIDED TUMOR RE
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B. Cutting planes The surgeon defin
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4.RESULTS To test the developed sys
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FROM PATIENT-SPECIFIC DATA TO MULTI
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catheterization mean measurements (
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the different virtual surgical desi
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1. ABSTRACT DIGITAL ULTRASOUND DESP
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2.2 Filtering Based Wavelet 2.2.1 C
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Table 1: quantitative criteria used
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Mural Thrombosis in a Two-Level Com
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But, the soft repulsive force can n
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Ratio of adhered PLT a simplificati
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DEGRADATION OF MAGNESIUM ALLOY STEN
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study and the parameter setting can
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Fig. 5. Damage evolution of the thr
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NUMERICAL SIMULATIONS OF FATIGUE FO
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Figure 1. Scheme of the two approac
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Figure 3. On the left, alternating
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INVESTIGATION OF HEAD-NECK KINEMATI
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complexity of the vertebrae and sku
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nearly no tension occurred for the
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9. Ito S, Ivancic PC, Panjabi MM, C
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[Ntsinjana et al., 2011], commonly
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impedances were maintained within p
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6. Pennati G., Corsini C., Cosentin
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analyse the effect that different a
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attached cases this value was highe
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References 1. Nordin M and Frankel
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therapy to achieve the desired medi
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iomechanical response of the leg to
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algorithm has to be integrated into
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to a modification in the tooth disp
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5. CONCLUSIONS 5.1 Geometry and per
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present work is to show the ability
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[6,7]. In order to reproduce numeri
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5. DISCUSSION, CONCLUSIONS AND PERS
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3.1 Generation of the vertebral sur
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3.4 Modeling of the facet joints Th
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The column diagramm of Fig.8 shows
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tool to evaluate the drug distribut
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Figure 3: The mean value of the dos
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INFLUENCE OF KYPHOSIS ON SPINAL LOA
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(a) (b) (c) Fig. 1. The three repre
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etween T6 and T9 with a higher degr
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A COMPARISON BETWEEN STANDARD AND D
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the SB with a 2.5 mm balloon; ii) o
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A TAWSS [Pa] B OSI [Pa] C 0 0.25 0.
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ABSTRACT CONSTITUTIVE MODELLING OF
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20% compression strains were impose
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4. DISCUSSION The limited number of
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AN ALGORITHM FOR MODELING THE FIBRE
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1 - Compute the centre of the botto
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(a) (b) Figure 2. Load-displacement
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A bio-mechanics based methodology t
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to a particular body part based on
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Injury Cost (USD) Million 0.7 0.6 0
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A SENSITIVITY ANALYSIS OF ADAPTIVE
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elationships can be found that rela
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Fig. 2: Percentage of bone volume w
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APPLICATION OF REACTION-DIFFUSION W
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AIRFLOW VENTILATION THROUGH HUMAN M
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solve all the governing equations.
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Fig. 4 Streamlines through the osti
Page 725 and 726:
MOLECULAR DYNAMICS SIMULATIONS FOR
Page 727 and 728:
COARSE-GRAINED MOLECULAR DYNAMICS S
Page 729 and 730:
DESIGN AND STRUCTURAL EVALUATION OF
Page 731 and 732: Figure 2 shows the optimal unit-cel
Page 733 and 734: ENUM (MPa) 100 90 80 70 60 50 40 30
Page 735 and 736: vivo menisco-tibial kinematics duri
Page 737 and 738: Loading the fully extended knee wit
Page 739 and 740: is also subject to variation due to
Page 741 and 742: environment in comparison to fixed
Page 743 and 744: 4. RESULTS AND DISCUSSION Convergen
Page 745 and 746: Because of the orthotropic assumpti
Page 747 and 748: 3D RECONSTRUCTION OF STENTED PORCIN
Page 749 and 750: Fluid model. The final configuratio
Page 751 and 752: Table 1: Computed slice measurement
Page 753 and 754: ANALYSIS OF THE EFFECT OF CONSIDERI
Page 755 and 756: For all these models, C1 = µ/2, µ
Page 757 and 758: the difference in percentage betwee
Page 759 and 760: A COMPUTATIONAL METHOD TO ESTIMATE
Page 761 and 762: C10, C01 and d were taken from [10]
Page 763 and 764: 4. RESULTS Fig. 2 shows the results
Page 765 and 766: COMPUTATIONAL AND EXPERIMENTAL MODE
Page 767 and 768: data using commercial software (Mim
Page 769 and 770: vitro (40 vs 34%), at the expense o
Page 771 and 772: FINITE ELEMENT ANALYSES OF IN VIVO
Page 773 and 774: The non-linear behaviour of the art
Page 775 and 776: Figure 6. Constant-life diagram for
Page 777 and 778: Optimal acceleration adjustment to
Page 779 and 780: , , , ,
Page 781: The vertical force bump observed du
Page 785 and 786: 3. MATERIAL AND METHODS 3.1 Experim
Page 787 and 788: from subjects S1, S2, S3, S5, and S
Page 789 and 790: APPLICATION OF A MODIFIED ELASTIC F
Page 791 and 792: h and h being the thickness of the
Page 793 and 794: 0.3 were used for the flat surface
Page 795 and 796: simulations of the mechanical respo
Page 797 and 798: 50000 images have been acquired. Th
Page 799 and 800: Fig.1 Modules of the proposed capsu
Page 801 and 802: 5. CONCLUSION This paper describes
Page 803 and 804: dependent on the implementation of
Page 805 and 806: joint computer model was driven wit
Page 807 and 808: otation. The AP laxity test showed
Page 809 and 810: A COMPUTATIONAL MODEL OF THE GROWTH
Page 811 and 812: where n p is the number of prolifer
Page 813 and 814: Hypertrophic columnar cartilage 0.2
Page 815 and 816: SIMULATION OF DAILY LIVING MOVEMENT
Page 817 and 818: otations were kept at zero, since t
Page 819 and 820: cavity (van der Helm, 1994). Howeve
Page 821 and 822: Solving Overconstrained Kinematic i
Page 823 and 824: 3.3. Muscles Muscles are modelled a
Page 825 and 826: 5. DISCUSSION A musculoskeletal num
Page 827 and 828: EFFECT OF OSCILATORY FLOW ON MORPHO
Page 829 and 830: dimensionless frequency . With the
Page 831 and 832: Wntsignaling, J Clin Invest., 2006,
Page 833 and 834:
Maximization (EM) algorithm witch e
Page 835 and 836:
4. RESULTS: n 1 2 x f ( x ; )
Page 837 and 838:
5. CONCLUSION In this work, a semi-
Page 839 and 840:
allow cell construct image inspecti
Page 841 and 842:
formula can be written as a linear
Page 843 and 844:
( ) (4) Poisson‟s ratio was assum
Page 845 and 846:
a) b) c) d) Figure 7 Validation: a)
Page 847 and 848:
DEVELOPMENT OF A NEW COMPUTATIONAL
Page 849 and 850:
The ScanIP wizard creates the new i
Page 851 and 852:
Fig. 5: Computer experiments: poste
Page 853 and 854:
A BIOMECHANICAL CONCEPT FOR CONSTRU
Page 855 and 856:
Figure 3. Construction of the radia
Page 857 and 858:
6. REFERENCES 1. Lees, S., A study
Page 859 and 860:
from cadaver surgeries were recreat
Page 861 and 862:
mean resection parameters and the p
Page 863 and 864:
5. DISCUSSION This study proposes a
Page 865 and 866:
simulations are evaluated by quanti
Page 867 and 868:
improvement of the shoulder prosthe
Page 869 and 870:
13. Coley B., Jolles B. M., Farron
Page 871 and 872:
simulations. Implicit in this setup
Page 873 and 874:
assigned zero fluid pressure bounda
Page 875 and 876:
the efficacy of predicting cellular
Page 877 and 878:
Another important function of the l
Page 879 and 880:
The insert (Fig. 3) is the part aga
Page 881 and 882:
changes due to the testing conditio
Page 883 and 884:
3. IN VIVO MEASURED LOAD COMPONENTS
Page 885 and 886:
anthropometric data - a data set fo
Page 887 and 888:
COMPUTATIONAL MODELING OF HIGHLY PO
Page 889 and 890:
objects smaller than one tenth of a
Page 891 and 892:
as 221.5 MPa. This value is more th
Page 893 and 894:
Macrostress and Macrostrain Finite
Page 895 and 896:
3.2. Extraction of individual artic
Page 897 and 898:
Unique strain patterns were observe
Page 899 and 900:
poroviscoelastic simulation of the
Page 901 and 902:
anchorage of the cartilage into a p
Page 903 and 904:
load of 0.5 N) resulted in a 55 kPa
Page 905 and 906:
properties as well as protect the h
Page 907 and 908:
Dynamic cell seeding combines two c
Page 909 and 910:
order (PB). The particles adhered (
Page 911 and 912:
2. D. Wendt, A. Marsano, M. Jakob,
Page 913 and 914:
2. Only a few high-level clinical s
Page 915 and 916:
A quasi-static analysis was perform
Page 917 and 918:
e increased by using stiffer or tig
Page 919 and 920:
Despite the importance of taking th
Page 921 and 922:
Table 2: Score chart presented to t
Page 923 and 924:
We conclude that the model develope
Page 925 and 926:
presented system - parallelization
Page 927 and 928:
image is projected to the subsequen
Page 929 and 930:
6. CONCLUSIONS The presented in the
Page 931 and 932:
first simulation uses data provided
Page 933 and 934:
Table 1: Models used in this study.
Page 935 and 936:
direction at knee extension, placin
Page 937 and 938:
3. METHODS 3.1. Model of heat trans
Page 939 and 940:
condition before and after heating.
Page 941 and 942:
during daily activities reported in
Page 943 and 944:
samples of brain tissue were extrac
Page 945 and 946:
5. DETERMINING MECHANICAL PROPERTIE
Page 947 and 948:
2001, Vol. 38 (4), 335-345. 8. Vela
Page 949 and 950:
chamber [4]. After obtaining the va
Page 951 and 952:
4. RESULTS 4.2 Surface and solid me
Page 953:
7. ACKNOWLEDGMENTS Financial fundin
Page 956 and 957:
affect crack penetration into osteo
Page 958 and 959:
Therefore, in order to examine the
Page 960 and 961:
3. Mischinski, S., Ural, A., 2011,
Page 962 and 963:
esearchers. The power of a finite-e
Page 964 and 965:
figure 2, we can determine the node
Page 966 and 967:
architecture, Muscle & Nerve, 2004,
Page 968 and 969:
ensure good short-term and long-ter
Page 970 and 971:
Table I - Micromotion results at th
Page 972 and 973:
COMBINED BONE-IMPLANT FIXATION: A P
Page 974 and 975:
FRICTIONAL PROPERTIES OF OSTEOARTHR
Page 976 and 977:
With the following boundary conditi
Page 978 and 979:
pressures higher than normal contac
Page 980 and 981:
1. ABSTRACT DYNAMIC PRESSURE RESPON
Page 982 and 983:
quasi-static solution, and both pos
Page 984 and 985:
(excluding the cadaveric validation
Page 987 and 988:
AN ANALYTICAL MODEL TO INVESTIGATE
Page 989 and 990:
K sh = 2. 3E sh 2 ( ) 2 1 2 1−ν
Page 991 and 992:
Fig. 7 modeling the oblique impact
Page 993 and 994:
A NON-LINEAR BIPHASIC MODEL FOR THE
Page 995 and 996:
system, it is convenient to write t
Page 997 and 998:
only with very small damping parame
Page 999 and 1000:
A PARAMETERIZED FE MODEL FOR SIMULA
Page 1001 and 1002:
the study of Polikeit et al. [10].
Page 1003 and 1004:
There are obvious limitations to ou
Page 1005 and 1006:
Abnormal stresses are often cited a
Page 1007 and 1008:
4. RESULTS The methods used to meas
Page 1009 and 1010:
that muscle imbalance associated wi
Page 1011 and 1012:
BIOCHEMICAL MODEL TO PREDICT THE ON
Page 1013 and 1014:
3.1 Model description The regulator
Page 1015 and 1016:
[3] Shier D., 2001, Hole’s Human
Page 1017 and 1018:
Biomechanics of Human Gluteal Tissu
Page 1019 and 1020:
information. Based on the indentati
Page 1021 and 1022:
t 1 ⎧⎪ ⎫ 2 2 ⎪ ττττ ( t
Page 1023 and 1024:
REFERENCES 1. Gefen A., Gefen N., L
Page 1025 and 1026:
analysis of the large-scale human m
Page 1027 and 1028:
λ σ = σ (8) act isom f f 0 ⋅
Page 1029 and 1030:
In the absence of membranes, the mu
Page 1031 and 1032:
predicted. This is possible for mod
Page 1033 and 1034:
-7.2 mN. The average value of the m
Page 1035:
efore the joint moment reaches zero
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