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

Author(s):  
Hannah J. Lundberg ◽  
Christopher B. Knowlton ◽  
Diego Orozco ◽  
Markus A. Wimmer

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.

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Tien Tuan Dao ◽  
Philippe Pouletaut

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.


2017 ◽  
Vol 139 (8) ◽  
Author(s):  
Marco A. Marra ◽  
Michael S. Andersen ◽  
Michael Damsgaard ◽  
Bart F. J. M. Koopman ◽  
Dennis Janssen ◽  
...  

Knowing the forces in the human body is of great clinical interest and musculoskeletal (MS) models are the most commonly used tool to estimate them in vivo. Unfortunately, the process of computing muscle, joint contact, and ligament forces simultaneously is computationally highly demanding. The goal of this study was to develop a fast surrogate model of the tibiofemoral (TF) contact in a total knee replacement (TKR) model and apply it to force-dependent kinematic (FDK) simulations of activities of daily living (ADLs). Multiple domains were populated with sample points from the reference TKR contact model, based on reference simulations and design-of-experiments. Artificial neural networks (ANN) learned the relationship between TF pose and loads from the medial and lateral sides of the TKR implant. Normal and right-turn gait, rising-from-a-chair, and a squat were simulated using both surrogate and reference contact models. Compared to the reference contact model, the surrogate contact model predicted TF forces with a root-mean-square error (RMSE) lower than 10 N and TF moments lower than 0.3 N·m over all simulated activities. Secondary knee kinematics were predicted with RMSE lower than 0.2 mm and 0.2 deg. Simulations that used the surrogate contact model ran on average three times faster than those using the reference model, allowing the simulation of a full gait cycle in 4.5 min. This modeling approach proved fast and accurate enough to perform extensive parametric analyses, such as simulating subject-specific variations and surgical-related factors in TKR.


2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Michael W. Hast ◽  
Stephen J. Piazza

Model-based estimation of in vivo contact forces arising between components of a total knee replacement is challenging because such forces depend upon accurate modeling of muscles, tendons, ligaments, contact, and multibody dynamics. Here we describe an approach to solving this problem with results that are tested by comparison to knee loads measured in vivo for a single subject and made available through the Grand Challenge Competition to Predict in vivo Tibiofemoral Loads. The approach makes use of a “dual-joint” paradigm in which the knee joint is alternately represented by (1) a ball-joint knee for inverse dynamic computation of required muscle controls and (2) a 12 degree-of-freedom (DOF) knee with elastic foundation contact at the tibiofemoral and patellofemoral articulations for forward dynamic integration. Measured external forces and kinematics were applied as a feedback controller and static optimization attempted to track measured knee flexion angles and electromyographic (EMG) activity. The resulting simulations showed excellent tracking of knee flexion (average RMS error of 2.53 deg) and EMG (muscle activations within ±10% envelopes of normalized measured EMG signals). Simulated tibiofemoral contact forces agreed qualitatively with measured contact forces, but their RMS errors were approximately 25% of the peak measured values. These results demonstrate the potential of a dual-joint modeling approach to predict joint contact forces from kinesiological data measured in the motion laboratory. It is anticipated that errors in the estimation of contact force will be reduced as more accurate subject-specific models of muscles and other soft tissues are developed.


Author(s):  
Hannah J. Lundberg ◽  
Markus A. Wimmer

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.


Thrombosis ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Lars C. Borris ◽  
Morten Breindahl ◽  
Michael R. Lassen ◽  
Ákos F. Pap

Prothrombin fragment 1+2 is excreted in urine (uF1+2) as a result of in vivo thrombin generation and can be a marker of coagulation status after an operative procedure. This study compared uF1+2 levels in patients with symptomatic and non-symptomatic venous thromboembolism (VTE) after total knee replacement (TKR) and in event-free sex- and age-matched controls. Significantly higher median uF1+2 levels were seen in the VTE patients on days 1, 3, and the day of venography (mostly day 7) after TKR compared with controls. The uF1+2 levels tended to be high in some patients with symptomatic VTE; however, the discriminatory efficacy of the test could not be evaluated. In conclusion, this study showed that patients with VTE tend to have significantly higher uF1+2 levels compared with patients without events between days 1 and 7 after TKR surgery. Measurement of uF1+2 could provide a simple, non-invasive clinical test to identify patients at risk of VTE.


2019 ◽  
Author(s):  
◽  
Swithin Samuel Razu

"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.


Author(s):  
Michael D Stokes ◽  
Brendan C Greene ◽  
Luke W Pietrykowski ◽  
Taylor M Gambon ◽  
Caroline E Bales ◽  
...  

Current total knee replacement designs work to address clinically desired knee stability and range of motion through a balance of retained anatomy and added implant geometry. However, simplified implant geometries such as bearing surfaces, posts, and cams are often used to replace complex ligamentous constraints that are sacrificed during most total knee replacement procedures. This article evaluates a novel total knee replacement design that incorporates synthetic ligaments to enhance the stability of the total knee replacement system. It was hypothesized that by incorporating artificial cruciate ligaments into a total knee replacement design at specific locations and lengths, the stability of the total knee replacement could be significantly altered while maintaining active ranges of motion. The ligament attachment mechanisms used in the design were evaluated using a tensile test, and determined to have a safety factor of three with respect to expected ligamentous loading in vivo. Following initial computational modeling of possible ligament orientations, a physical prototype was constructed to verify the function of the design by performing anterior/posterior drawer tests under physiologic load. Synthetic ligament configurations were found to increase total knee replacement stability up to 94% compared to the no-ligament case, while maintaining total knee replacement flexion range of motion between 0° and 120°, indicating that a total knee replacement that incorporates synthetic ligaments with calibrated location and lengths should be able to significantly enhance and control the kinematic performance of a total knee replacement system.


The Knee ◽  
2004 ◽  
Vol 11 (3) ◽  
pp. 183-187 ◽  
Author(s):  
C.F Kellett ◽  
A Short ◽  
A Price ◽  
H.S Gill ◽  
D.W Murray

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