![]() The other two named methods, calculating external joint moments and internal joint contact forces, are therefore used in a more dynamic environment when younger study cohorts and other dynamic movements except for walking are investigated. Additionally, highly dynamic movements like side-cutting have not been investigated in patients with instrumented prosthesis. Patients with instrumented prostheses are rare 15, 16, and their loading patterns may not be representative of other populations of interest, like children. In vivo measurement of joint contact force can only be done by invasive methods as an instrumented prosthesis 14. Nevertheless, both methods are estimations of the loading in a joint 13. Hence, internal joint contact forces provide a more accurate measure of joint loading compared to joint moments during dynamic tasks as walking. ![]() Estimating internal joint contact forces with musculoskeletal models include the contribution of all internal forces such as muscles and ligaments (when present in the model). Therefore, the calculation of joint moments has the advantage of quick availability and lower cost in terms of time or human capacity. Calculating the internal joint contact, muscle and/or tendon forces require additional time and expertise 1, 11, 12. Linear models that use both the KAM and KFM as covariates have higher correlations with KCF than models that use KAM alone 8, 9, 10. ![]() The external knee flexion/extension moment (KFM/KEM) also contributes to the internal knee joint contact force (KCF). Joint moments are usually available almost directly after the movement analysis because joint moment output calculated by inverse dynamics is often implemented in the standard data acquisition software 7. ![]() Both methods for estimating joint loading demonstrate advantages: joint moments are easily calculated, but knee joint contact forces are more representative of cartilage loading 6. They are a part of the internal load and mainly generated by muscles during walking 4, 5. Calculating joint contact forces require the additional use of musculoskeletal simulation software. The knee adduction moment (KAM) is a commonly used surrogate measure for medial compartment knee loading because it was statistically associated to osteoarthritis (OA) severity and progression 2, 3 and is relatively simple to compute. In the last five years the number of studies has tripled (see supplementary material for the full search terms used in Pubmed) that performed sports or clinical gait analysis and investigated internal joint contact or muscle forces rather than joint moments 1. In the future, these models could be used to evaluate peak knee joint contact forces from musculoskeletal simulations using peak joint moments from motion capture software, obviating the need for time-consuming musculoskeletal simulations. The knee flexion and adduction moments were significant covariates in the models, strengthening the understanding of the statistical relationship between both moments and medial and lateral knee joint contact forces. Peak knee joint moments were strongly correlated ( R 2 > 0.85, p < 0.001) with both peak medial and lateral knee joint contact forces. The purpose of this study was to evaluate how accurately model-based predictions of peak medial and lateral knee joint contact forces during walking could be estimated by linear mixed-effects models including joint moments for children and adolescents with and without valgus malalignment. Statistical models have shown promising correlations between medial knee joint contact forces and knee adduction moments in particularly in individuals with knee osteoarthritis or after total knee replacements ( R 2 = 0.44–0.60). However, joint loading is often evaluated with surrogate measures, like the external knee adduction moment, due to the complexity of computing joint contact forces. Compressive knee joint contact force during walking is thought to be related to initiation and progression of knee osteoarthritis.
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