scholarly journals Dynamic Knee Joint Line Orientation Is Not Predictive of Tibio-Femoral Load Distribution During Walking

2021 ◽  
Vol 9 ◽  
Author(s):  
Adam Trepczynski ◽  
Philippe Moewis ◽  
Philipp Damm ◽  
Pascal Schütz ◽  
Jörn Dymke ◽  
...  
Keyword(s):  
Knee Joint ◽  
Strong Correlation ◽  
Load Distribution ◽  
Joint Line ◽  
Force Distribution ◽  
Ground Reaction Forces ◽  
Joint Loading ◽  
Internal Joint ◽  
Reaction Forces ◽  
Dynamic Alignment

Some approaches in total knee arthroplasty aim for an oblique joint line to achieve an even medio-lateral load distribution across the condyles during the stance phase of gait. While there is much focus on the angulation of the joint line in static frontal radiographs, precise knowledge of the associated dynamic joint line orientation and the internal joint loading is limited. The aim of this study was to analyze how static alignment in frontal radiographs relates to dynamic alignment and load distribution, based on direct measurements of the internal joint loading and kinematics. A unique and novel combination of telemetrically measured in vivo knee joint loading and simultaneous internal joint kinematics derived from mobile fluoroscopy (“CAMS-Knee dataset”) was employed to access the dynamic alignment and internal joint loading in 6 TKA patients during level walking. Static alignment was measured in standard frontal postoperative radiographs while external adduction moments were computed based on ground reaction forces. Both static and dynamic parameters were analyzed to identify correlations using linear and non-linear regression. At peak loading during gait, the joint line was tilted laterally by 4°–7° compared to the static joint line in most patients. This dynamic joint line tilt did not show a strong correlation with the medial force (R2: 0.17) or with the mediolateral force distribution (pseudo R2: 0.19). However, the external adduction moment showed a strong correlation with the medial force (R2: 0.85) and with the mediolateral force distribution (pseudo R2: 0.78). Alignment measured in static radiographs has only limited predictive power for dynamic kinematics and loading, and even the dynamic orientation of the joint line is not an important factor for the medio-lateral knee load distribution. Preventive and rehabilitative measures should focus on the external knee adduction moment based on the vertical and horizontal components of the ground reaction forces.

scholarly journals Development and Validation of a 3-D Model to Predict Knee Joint Loading During Dynamic Movement

2003 ◽  
Vol 125 (6) ◽  
pp. 864-874 ◽  
Author(s):  
S. G. McLean ◽  
A. Su ◽  
A. J. van den Bogert
Keyword(s):  
Knee Joint ◽  
Lower Extremity ◽  
Neuromuscular Control ◽  
Muscle Stimulation ◽  
Ground Reaction Forces ◽  
Joint Loading ◽  
Reaction Forces ◽  
Optimized Model ◽  
D Model ◽  
Knee Joint Loading

The purpose of this study was to develop a subject-specific 3-D model of the lower extremity to predict neuromuscular control effects on 3-D knee joint loading during movements that can potentially cause injury to the anterior cruciate ligament (ACL) in the knee. The simulation consisted of a forward dynamic 3-D musculoskeletal model of the lower extremity, scaled to represent a specific subject. Inputs of the model were the initial position and velocity of the skeletal elements, and the muscle stimulation patterns. Outputs of the model were movement and ground reaction forces, as well as resultant 3-D forces and moments acting across the knee joint. An optimization method was established to find muscle stimulation patterns that best reproduced the subject’s movement and ground reaction forces during a sidestepping task. The optimized model produced movements and forces that were generally within one standard deviation of the measured subject data. Resultant knee joint loading variables extracted from the optimized model were comparable to those reported in the literature. The ability of the model to successfully predict the subject’s response to altered initial conditions was quantified and found acceptable for use of the model to investigate the effect of altered neuromuscular control on knee joint loading during sidestepping. Monte Carlo simulations (N=100,000) using randomly perturbed initial kinematic conditions, based on the subject’s variability, resulted in peak anterior force, valgus torque and internal torque values of 378 N, 94 Nm and 71 Nm, respectively, large enough to cause ACL rupture. We conclude that the procedures described in this paper were successful in creating valid simulations of normal movement, and in simulating injuries that are caused by perturbed neuromuscular control.

scholarly journals Machine Learning-Based Estimation of Ground Reaction Forces and Knee Joint Kinetics from Inertial Sensors While Performing a Vertical Drop Jump

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7709
Author(s):  
Serena Cerfoglio ◽  
Manuela Galli ◽  
Marco Tarabini ◽  
Filippo Bertozzi ◽  
Chiarella Sforza ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Knee Joint ◽  
Field Analysis ◽  
Ground Reaction Forces ◽  
Drop Jump ◽  
Joint Moments ◽  
Data Set ◽  
Joint Kinetics ◽  
Reaction Forces

Nowadays, the use of wearable inertial-based systems together with machine learning methods opens new pathways to assess athletes’ performance. In this paper, we developed a neural network-based approach for the estimation of the Ground Reaction Forces (GRFs) and the three-dimensional knee joint moments during the first landing phase of the Vertical Drop Jump. Data were simultaneously recorded from three commercial inertial units and an optoelectronic system during the execution of 112 jumps performed by 11 healthy participants. Data were processed and sorted to obtain a time-matched dataset, and a non-linear autoregressive with external input neural network was implemented in Matlab. The network was trained through a train-test split technique, and performance was evaluated in terms of Root Mean Square Error (RMSE). The network was able to estimate the time course of GRFs and joint moments with a mean RMSE of 0.02 N/kg and 0.04 N·m/kg, respectively. Despite the comparatively restricted data set and slight boundary errors, the results supported the use of the developed method to estimate joint kinetics, opening a new perspective for the development of an in-field analysis method.

scholarly journals A Systematic Review of the Associations Between Inverse Dynamics and Musculoskeletal Modeling to Investigate Joint Loading in a Clinical Environment

2020 ◽  
Vol 8 ◽  
Author(s):  
Jana Holder ◽  
Ursula Trinler ◽  
Andrea Meurer ◽  
Felix Stief
Keyword(s):  
Knee Joint ◽  
Clinical Decision Making ◽  
Inverse Dynamics ◽  
Clinical Decision ◽  
Contact Forces ◽  
Musculoskeletal Modeling ◽  
Joint Loading ◽  
Joint Moments ◽  
Internal Joint ◽  
Joint Contact

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.

Musculoskeletal Model of the Human Knee With Representation of Menisci During the Stance Phase of a Walk Cycle

2012 ◽  
Author(s):  
Mohammad Kia ◽  
Trent M. Guess ◽  
Antonis Stylianou
Keyword(s):  
Knee Joint ◽  
Stance Phase ◽  
Musculoskeletal Model ◽  
Musculoskeletal Modeling ◽  
Ground Reaction Forces ◽  
Forward Dynamics ◽  
Muscle Forces ◽  
Human Knee ◽  
Reaction Forces ◽  
Movement Simulation

Movement simulation and musculoskeletal modeling can predict muscle forces, but current methods are hindered by simplified representations of joint structures. Simulations that incorporate muscle forces, an anatomical representation of the natural knee, and contact mechanics would be a powerful tool in orthopedics. This study combined a validated anatomical model of a knee joint with menisci and a musculoskeletal model of the human lower extremity. A forward-dynamics muscle driven simulation of the stance phase of a walk cycle was simulated in LifeMOD (Lifemodeler, Inc) and muscle forces and ground reaction forces were estimated. The predicted forces were evaluated using test data provided by Vaughan CL. et al. (1999).

Normative data of knee joint motion and ground reaction forces in adult level walking

1983 ◽  
Vol 16 (3) ◽  
pp. 219-233 ◽  
Author(s):  
E.Y. Chao ◽  
R.K. Laughman ◽  
E. Schneider ◽  
R.N. Stauffer
Keyword(s):  
Knee Joint ◽  
Normative Data ◽  
Ground Reaction Forces ◽  
Joint Motion ◽  
Adult Level ◽  
Level Walking ◽  
Knee Joint Motion ◽  
Reaction Forces
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