scholarly journals Individual muscle contributions to the axial knee joint contact force during normal walking

2010 ◽  
Vol 43 (14) ◽  
pp. 2780-2784 ◽  
Author(s):  
Kotaro Sasaki ◽  
Richard R. Neptune
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Normal Walking ◽  
Individual Muscle ◽  
Joint Contact Force ◽  
Joint Contact

Prediction of Knee Joint Contact Forces From External Measures Using Principal Component Prediction and Reconstruction

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
Keyword(s):  
Knee Joint ◽  
Knee Osteoarthritis ◽  
Real Time ◽  
Contact Force ◽  
Haptic Feedback ◽  
Principal Component ◽  
Contact Forces ◽  
Statistical Regression ◽  
Joint Contact Force ◽  
Joint Contact

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.

Soldier-relevant body borne loads increase knee joint contact force during a run-to-stop maneuver

2016 ◽  
Vol 49 (16) ◽  
pp. 3868-3874 ◽  
Author(s):  
John W. Ramsay ◽  
Clifford L. Hancock ◽  
Meghan P. O’Donovan ◽  
Tyler N. Brown
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Joint Contact Force ◽  
Joint Contact

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.

The Effect of Surface Inclination to Knee Joint Contact Force: A Pilot Study

2021 ◽  
pp. 729-736
Author(s):  
Noor Arifah Azwani Abdul Yamin ◽  
Khairul Salleh Basaruddin ◽  
Ahmad Faizal Salleh ◽  
Ruslizam Daud ◽  
Mohd Hanafi Mat Som
Keyword(s):  
Pilot Study ◽  
Knee Joint ◽  
Contact Force ◽  
Joint Contact Force ◽  
Joint Contact ◽  
Surface Inclination ◽  
Effect Of Surface

scholarly journals Minimum detectable change for knee joint contact force estimates using an EMG-driven model

2013 ◽  
Vol 38 (4) ◽  
pp. 1051-1053 ◽  
Author(s):  
Emily S. Gardinier ◽  
Kurt Manal ◽  
Thomas S. Buchanan ◽  
Lynn Snyder-Mackler
Keyword(s):  
Knee Joint ◽  
Contact Force ◽  
Detectable Change ◽  
Minimum Detectable Change ◽  
Joint Contact Force ◽  
Joint Contact
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