The Effect of the Tibiofemoral Contact Path Centroid Location on TKR Contact Forces

2010 ◽  
Author(s):  
Hannah J. Lundberg ◽  
Markus A. Wimmer
Keyword(s):  
Knee Joint ◽  
Tibial Plateau ◽  
Soft Tissues ◽  
Three Dimensional ◽  
Solution Space ◽  
Contact Forces ◽  
Detailed Knowledge ◽  
Joint Contact ◽  
Total Knee

Detailed knowledge of in vivo knee contact forces and the contribution from muscles, ligaments, and other soft-tissues to knee joint function are essential for evaluating total knee replacement (TKR) designs. We have recently developed a mathematical model for calculating knee joint contact forces using parametric methodology (Lundberg et al., 2009). The numerical model calculates a “solution space” of three-dimensional contact forces for both the medial and lateral compartments of the tibial plateau. The solution spaces are physiologically meaningful, and represent the result of balancing the external moments and forces by different strategies.

Grand Challenge Competition: A Parametric Numerical Model to Predict In Vivo Medial and Lateral Knee Forces in Walking Gaits

2012 ◽  
Author(s):  
Christopher B. Knowlton ◽  
Markus A. Wimmer ◽  
Hannah J. Lundberg
Keyword(s):  
Knee Joint ◽  
Computational Models ◽  
Soft Tissues ◽  
Numerical Models ◽  
Contact Forces ◽  
Grand Challenge ◽  
Total Knee Replacements ◽  
Lateral Contact ◽  
Total Knee

Numerical models are necessary to estimate forces through the knee joint during activities of daily living. However, the numerous muscles and soft tissues crossing the knee joint result in a computationally indeterminate problem. The recent availability of measured contact force data from telemeterized total knee replacements (TKRs) has given researchers the chance to validate models, but telemeterized TKRs represent only a few patients with a specific implant type. Computational models remain necessary to bridge the gap between the small instrumented patient population with a particular implant and larger patient populations executing various activities. Abstracted gait data from another lab tests the versatility of any model to accurately predict forces of TKR patients performing a variety of gaits with disparate implant types. In this study, we calculate and examine the differences between medial and lateral contact forces in level walking and medial thrust gait trials from a freely provided dataset1.

A Weighted Objective Function Reduces Estimates of Medial and Lateral Knee Joint Contact Loads During Gait

2011 ◽  
Author(s):  
S. C. E. Brandon ◽  
D. G. Thelen ◽  
K. J. Deluzio
Keyword(s):  
Knee Joint ◽  
Tibial Plateau ◽  
Soft Tissues ◽  
Grand Challenge ◽  
Contact Loads ◽  
Joint Contact ◽  
Reaction Forces ◽  
Six Degree Of Freedom ◽  
Knee Pathology

Accurate prediction of knee joint contact loading during gait is important for understanding knee pathology and development of suitable clinical interventions. While many researchers have modeled the knee contact loads during level walking, these predictions have ranged from 3.4 [1] to 7 [2] times body weight. Validation of contact loads is difficult; the joint contact load depends not only on readily obtainable external kinematics and reaction forces, but also on the forces generated by muscle and other soft tissues. Recently, an instrumented tibial implant, capable of telemetrically reporting the six degree-of-freedom loading environment of the tibial plateau, was used to tune and validate an EMG-driven model of the lower extremity [3]. Recognizing the value of these in vivo data, and the limitations of existing knee models, these researchers devised the Grand Challenge Competitions to Predict In Vivo Knee Loads.

Calculated Axial Forces at the Knee in Total Knee Replacement Patients During Chair and Stair Activities

2012 ◽  
Author(s):  
Hannah J. Lundberg ◽  
Christopher B. Knowlton ◽  
Diego Orozco ◽  
Markus A. Wimmer
Keyword(s):  
Total Knee Replacement ◽  
Knee Replacement ◽  
Contact Forces ◽  
Force Output ◽  
Stair Ascent ◽  
Numeric Model ◽  
Axial Forces ◽  
Joint Contact ◽  
Total Knee

Knowledge of in vivo knee contact forces is essential for evaluating total knee replacement (TKR) designs. This is particularly true for activities other than walking, because there is still a limited understanding of its impact on wear. It has been shown that wear scars from retrieved implants have obvious differences compared with simulator tested components in both size of worn area and in damage mode. The divergence could be related to the omission of other activities than walking when testing components in the simulator. The purpose of this study was to use a parametric numerical model for predicting joint contact forces during stair ascent/descent and chair sitting/rising and compare those to measured forces from a database. We hypothesized that the contact force output of the numeric model would be similar to the measured forces.

scholarly journals Prediction of knee loading in native knee and total knee arthroplasty : a forward dynamics computational study

2019 ◽  
Author(s):  
◽  
Swithin Samuel Razu
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Musculoskeletal Model ◽  
Contact Forces ◽  
Muscle Forces ◽  
Model Predictions ◽  
Subject Specific ◽  
Joint Contact ◽  
Total Knee

"The goal of this dissertation is to develop a musculoskeletal model and corroborate model predictions to experimentally measured in vivo knee contact forces, in order to study the biomechanical consequences of two different total knee arthroplasty designs. The two main contributions of this dissertation are: (1) Corroboration to experimental data: The development of an EMG-driven, full-body, musculoskeletal model with subject-specific leg geometries including deformable contacts, ligaments, 6DOF knee joint, and a shoe-floor model that can concurrently predict muscle forces, ligament forces, and joint contact forces. Model predictions of tibiofemoral joint contact forces were evaluated against the subject-specific in vivo measurements from the instrumented TKR for three distinctly different styles of over ground gait. (2) Virtual surgery in TKA: The musculoskeletal modeling methodology was then used to develop a model for one healthy participant with a native knee and then virtually replacing the native knee with fixed-bearing and mobile-bearing total knee arthroplasty designs performing gait and step-up tasks. This approach minimized the biomechanical impact of variations in sex, geometry, implant size, design and positioning, ligament location and tension, and muscle forces found across patients. The differences in biomechanics were compared for the two designs. 1.2 Significance of this Research The world health organization ranks musculoskeletal disorders as the second largest contributor to disability worldwide. Conservative estimates put the national cost of direct care for musculoskeletal disease at $212.7 billion a year [1]. Many people who suffer from neuromuscular or musculoskeletal diseases may benefit from the insights gained from surgery simulations, since musculoskeletal reconstructions are commonly performed on these individuals. Improved surgical outcomes will benefit these individuals not only in the short-term, but also in the long-term, since their future rehabilitation needs may be reduced. For example, although total knee arthroplasty is a common surgical procedure for the treatment of osteoarthritis with over 700,000 procedures performed each year [2], many patients are unhappy with the ultimate results [3]. Ten to 30% of patients report [4] pain, dissatisfaction with function, and the need for further surgery such as revision after the initial surgery resulting in costs exceeding $11 billion [5]. Potentially, simulation studies that quantify the important biomechanical variables will reduce the need for revision surgeries in patients."--Introduction.

Comparison of Numerically Modeled Knee Joint Contact Forces to Instrumented Total Knee Prosthesis Forces

2009 ◽  
Author(s):  
Hannah J. Lundberg ◽  
Kharma C. Foucher ◽  
Thomas P. Andriacchi ◽  
Markus A. Wimmer
Keyword(s):  
Mathematical Model ◽  
Input Data ◽  
Muscle Activation ◽  
Solution Space ◽  
Contact Forces ◽  
Functional Mobility ◽  
Joint Disease ◽  
Valuable Insight ◽  
Total Knee

Total knee replacement (TKR) surgery decreases pain and increases functional mobility for patients with joint disease. As primary TKRs are implanted in patients who are younger, heavier, and more active (1), increases in wear and TKR revision rates are expected. Preclinical analysis of TKRs with mathematical models and experimental tests require accurate in vivo kinetic and kinematic input data. Kinematics can be obtained with gait analysis, but in vivo force data are just beginning to become available from instrumented TKRs from only a few patients (2). Patient gait is highly variable both within and between individuals and can be influenced by a variety of factors including the progression and history of joint disease, surgical procedure, and TKR design. Variation in patient gait and activities results in subsequent contact force and polyethylene wear variability. A validated mathematical model which calculates contact forces for alternate input data could add valuable insight for preclinical testing. A problem facing mathematical modeling is that there are too many unknowns to directly solve for contact forces. In order to approach this problem, we have developed a knee mathematical model that allows parametric variation of muscle activation levels (3) and calculates a solution space of physically possible contact forces.

scholarly journals An Electromyogram-Driven Musculoskeletal Model of the Knee to Predict in Vivo Joint Contact Forces During Normal and Novel Gait Patterns

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Kurt Manal ◽  
Thomas S. Buchanan
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Contact Forces ◽  
Grand Challenge ◽  
Normal Walking ◽  
Gait Patterns ◽  
Internal Joint ◽  
Model Predictions ◽  
Joint Contact

Computational models that predict internal joint forces have the potential to enhance our understanding of normal and pathological movement. Validation studies of modeling results are necessary if such models are to be adopted by clinicians to complement patient treatment and rehabilitation. The purposes of this paper are: (1) to describe an electromyogram (EMG)-driven modeling approach to predict knee joint contact forces, and (2) to evaluate the accuracy of model predictions for two distinctly different gait patterns (normal walking and medial thrust gait) against known values for a patient with a force recording knee prosthesis. Blinded model predictions and revised model estimates for knee joint contact forces are reported for our entry in the 2012 Grand Challenge to predict in vivo knee loads. The EMG-driven model correctly predicted that medial compartment contact force for the medial thrust gait increased despite the decrease in knee adduction moment. Model accuracy was high: the difference in peak loading was less than 0.01 bodyweight (BW) with an R2 = 0.92. The model also predicted lateral loading for the normal walking trial with good accuracy exhibiting a peak loading difference of 0.04 BW and an R2 = 0.44. Overall, the EMG-driven model captured the general shape and timing of the contact force profiles and with accurate input data the model estimated joint contact forces with sufficient accuracy to enhance the interpretation of joint loading beyond what is possible from data obtained from standard motion capture studies.

A Subject-Specific Musculoskeletal Modeling Framework to Predict In Vivo Mechanics of Total Knee Arthroplasty

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Marco A. Marra ◽  
Valentine Vanheule ◽  
René Fluit ◽  
Bart H. F. J. M. Koopman ◽  
John Rasmussen ◽  
...  
Keyword(s):  
Knee Kinematics ◽  
Contact Forces ◽  
Grand Challenge ◽  
Modeling Framework ◽  
Trial Simulation ◽  
Subject Specific ◽  
Joint Contact ◽  
Total Knee ◽  
The Right

Musculoskeletal (MS) models should be able to integrate patient-specific MS architecture and undergo thorough validation prior to their introduction into clinical practice. We present a methodology to develop subject-specific models able to simultaneously predict muscle, ligament, and knee joint contact forces along with secondary knee kinematics. The MS architecture of a generic cadaver-based model was scaled using an advanced morphing technique to the subject-specific morphology of a patient implanted with an instrumented total knee arthroplasty (TKA) available in the fifth “grand challenge competition to predict in vivo knee loads” dataset. We implemented two separate knee models, one employing traditional hinge constraints, which was solved using an inverse dynamics technique, and another one using an 11-degree-of-freedom (DOF) representation of the tibiofemoral (TF) and patellofemoral (PF) joints, which was solved using a combined inverse dynamic and quasi-static analysis, called force-dependent kinematics (FDK). TF joint forces for one gait and one right-turn trial and secondary knee kinematics for one unloaded leg-swing trial were predicted and evaluated using experimental data available in the grand challenge dataset. Total compressive TF contact forces were predicted by both hinge and FDK knee models with a root-mean-square error (RMSE) and a coefficient of determination (R2) smaller than 0.3 body weight (BW) and equal to 0.9 in the gait trial simulation and smaller than 0.4 BW and larger than 0.8 in the right-turn trial simulation, respectively. Total, medial, and lateral TF joint contact force predictions were highly similar, regardless of the type of knee model used. Medial (respectively lateral) TF forces were over- (respectively, under-) predicted with a magnitude error of M < 0.2 (respectively > −0.4) in the gait trial, and under- (respectively, over-) predicted with a magnitude error of M > −0.4 (respectively < 0.3) in the right-turn trial. Secondary knee kinematics from the unloaded leg-swing trial were overall better approximated using the FDK model (average Sprague and Geers' combined error C = 0.06) than when using a hinged knee model (C = 0.34). The proposed modeling approach allows detailed subject-specific scaling and personalization and does not contain any nonphysiological parameters. This modeling framework has potential applications in aiding the clinical decision-making in orthopedics procedures and as a tool for virtual implant design.

Tibio-Femoral Contact Pressure During Gait

2013 ◽  
Author(s):  
Antonis P. Stylianou ◽  
Mohammad Kia ◽  
Trent M. Guess
Keyword(s):  
Knee Joint ◽  
Total Knee Replacement ◽  
Articular Surface ◽  
Contact Forces ◽  
Ideal Tool ◽  
Total Knee ◽  
Ambulatory Activities ◽  
Knee Joint Loading ◽  
The Ideal

Detailed analysis of knee joint loading during ambulatory activities is of utmost importance for improving the design of total knee replacement components and the outcome of the surgical procedures. A dynamic computational model capable of concurrent predictions of muscle, ligament, and articular surface contact forces would be the ideal tool for enhancing our knowledge of these in-vivo loads and for exploring different loading scenarios.

scholarly journals A Hertzian Integrated Contact Model of the Total Knee Replacement Implant for the Estimation of Joint Contact Forces

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Tien Tuan Dao ◽  
Philippe Pouletaut
Keyword(s):  
Total Knee Replacement ◽  
Elastic Properties ◽  
Knee Replacement ◽  
Material Properties ◽  
Contact Forces ◽  
Contact Model ◽  
Patient Specific ◽  
Joint Contact ◽  
Total Knee

The prediction of lower limb muscle and contact forces may provide useful knowledge to assist the clinicians in the diagnosis as well as in the development of appropriate treatment for musculoskeletal disorders. Research studies have commonly estimated joint contact forces using model-based muscle force estimation due to the lack of a reliable contact model and material properties. The objective of this present study was to develop a Hertzian integrated contact model. Then, in vivo elastic properties of the Total Knee Replacement (TKR) implant were identified using in vivo contact forces leading to providing reliable material properties for modeling purposes. First, a patient specific rigid musculoskeletal model was built. Second, a STL-based implant model was designed to compute the contact area evolutions during gait motions. Finally, a Hertzian integrated contact model was defined for the in vivo identification of elastic properties (Young’s modulus and Poisson coefficient) of the instrumented TKR implant. Our study showed a potential use of a new approach to predict the contact forces without knowledge of muscle forces. Thus, the outcomes may lead to accurate and reliable prediction of human joint contact forces for new case study.

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