Frontal Plane Tibiofemoral Alignment is Strongly Related to Compartmental Knee Joint Contact Forces and Muscle Control Strategies During Stair Ascent

2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Hunter J. Bennett ◽  
Joshua T. Weinhandl ◽  
Kristina Fleenor ◽  
Songning Zhang

Static frontal plane tibiofemoral alignment is an important factor in dynamic knee alignment and knee adduction moments (KAMs). However, little is known about the relationship between alignment and compartment contact forces or muscle control strategies. The purpose of this study was to estimate medial (MCF) and lateral (LCF) compartment knee joint contact forces and muscle forces during stair ascent using a musculoskeletal model implementing subject-specific knee alignments. Kinematic and kinetic data from 20 healthy individuals with radiographically confirmed varus or valgus knee alignments were simulated using alignment specific models to predict MCFs and LCFs. Muscle forces were determined using static optimization. Independent samples t-tests compared contact and muscle forces between groups during weight acceptance and during pushoff. The varus group exhibited increased weight acceptance peak MCFs, while the valgus group exhibited increased pushoff peak LCFs. The varus group utilized increased vasti muscle forces during weight acceptance and adductor forces during pushoff. The valgus group utilized increased abductor forces during pushoff. The alignment-dependent contact forces provide evidence of the significance of frontal plane knee alignment in healthy individuals, which may be important in considering future knee joint health. The differing muscle control strategies between alignments detail-specific neuromuscular responses to control frontal plane knee loads.

2018 ◽  
Vol 34 (5) ◽  
pp. 419-423 ◽  
Author(s):  
Christopher M. Saliba ◽  
Allison L. Clouthier ◽  
Scott C.E. Brandon ◽  
Michael J. Rainbow ◽  
Kevin J. Deluzio

Abnormal loading of the knee joint contributes to the pathogenesis of knee osteoarthritis. Gait retraining is a noninvasive intervention that aims to reduce knee loads by providing audible, visual, or haptic feedback of gait parameters. The computational expense of joint contact force prediction has limited real-time feedback to surrogate measures of the contact force, such as the knee adduction moment. We developed a method to predict knee joint contact forces using motion analysis and a statistical regression model that can be implemented in near real-time. Gait waveform variables were deconstructed using principal component analysis, and a linear regression was used to predict the principal component scores of the contact force waveforms. Knee joint contact force waveforms were reconstructed using the predicted scores. We tested our method using a heterogenous population of asymptomatic controls and subjects with knee osteoarthritis. The reconstructed contact force waveforms had mean (SD) root mean square differences of 0.17 (0.05) bodyweight compared with the contact forces predicted by a musculoskeletal model. Our method successfully predicted subject-specific shape features of contact force waveforms and is a potentially powerful tool in biofeedback and clinical gait analysis.


Author(s):  
Jana Holder ◽  
Ursula Trinler ◽  
Andrea Meurer ◽  
Felix Stief

The assessment of knee or hip joint loading by external joint moments is mainly used to draw conclusions on clinical decision making. However, the correlation between internal and external loads has not been systematically analyzed. This systematic review aims, therefore, to clarify the relationship between external and internal joint loading measures during gait. A systematic database search was performed to identify appropriate studies for inclusion. In total, 4,554 articles were identified, while 17 articles were finally included in data extraction. External joint loading parameters were calculated using the inverse dynamics approach and internal joint loading parameters by musculoskeletal modeling or instrumented prosthesis. It was found that the medial and total knee joint contact forces as well as hip joint contact forces in the first half of stance can be well predicted using external joint moments in the frontal plane, which is further improved by including the sagittal joint moment. Worse correlations were found for the peak in the second half of stance as well as for internal lateral knee joint contact forces. The estimation of external joint moments is useful for a general statement about the peak in the first half of stance or for the maximal loading. Nevertheless, when investigating diseases as valgus malalignment, the estimation of lateral knee joint contact forces is necessary for clinical decision making because external joint moments could not predict the lateral knee joint loading sufficient enough. Dependent on the clinical question, either estimating the external joint moments by inverse dynamics or internal joint contact forces by musculoskeletal modeling should be used.


2018 ◽  
Vol 34 (4) ◽  
pp. 336-341 ◽  
Author(s):  
Stefan Sebastian Tomescu ◽  
Ryan Bakker ◽  
Tyson A.C. Beach ◽  
Naveen Chandrashekar

Estimation of muscle forces through musculoskeletal simulation is important in understanding human movement and injury. Unmatched filter frequencies used to low-pass filter marker and force platform data can create artifacts during inverse dynamics analysis, but their effects on muscle force calculations are unknown. The objective of this study was to determine the effects of filter cutoff frequency on simulation parameters and magnitudes of lower-extremity muscle and resultant joint contact forces during a high-impact maneuver. Eight participants performed a single-leg jump landing. Kinematics was captured with a 3D motion capture system, and ground reaction forces were recorded with a force platform. The marker and force platform data were filtered using 2 matched filter frequencies (10–10 Hz and 15–15 Hz) and 2 unmatched filter frequencies (10–50 Hz and 15–50 Hz). Musculoskeletal simulations using computed muscle control were performed in OpenSim. The results revealed significantly higher peak quadriceps (13%), hamstrings (48%), and gastrocnemius forces (69%) in the unmatched (10–50 Hz and 15–50 Hz) conditions than in the matched (10–10 Hz and 15–15 Hz) conditions (P < .05). Resultant joint contact forces and reserve (nonphysiologic) moments were similarly larger in the unmatched filter categories (P < .05). This study demonstrated that artifacts created from filtering with unmatched filter cutoffs result in altered muscle forces and dynamics that are not physiologic.


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.


Author(s):  
Justin W. Fernandez ◽  
Hyung J. Kim ◽  
Massoud Akbarshahi ◽  
Jonathan P. Walter ◽  
Benjamin J. Fregly ◽  
...  

Many studies have used musculoskeletal models to predict in vivo muscle forces at the knee during gait [1, 2]. Unfortunately, quantitative assessment of the model calculations is often impracticable. Various indirect methods have been used to evaluate the accuracy of model predictions, including comparisons against measurements of muscle activity, joint kinematics, ground reaction forces, and joint moments. In a recent study, an instrumented hip implant was used to validate calculations of hip contact forces directly [3]. The same model was subsequently used to validate model calculations of tibiofemoral loading during gait [4]. Instrumented knee implants have also been used in in vitro and in vivo studies to quantify differences in biomechanical performance between various TKR designs [5, 6]. The main aim of the present study was to evaluate model predictions of knee muscle forces by direct comparison with measurements obtained from an instrumented knee implant. Calculations of muscle and joint-contact loading were performed for level walking at slow, normal, and fast speeds.


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.


2020 ◽  
Vol 28 ◽  
pp. S250-S251
Author(s):  
J.B. Bowd ◽  
S. van Rossom ◽  
M. De Vecchis ◽  
D. Williams ◽  
C. Wilson ◽  
...  

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