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Return to sports following total hip arthroplasty (THA) is important to an increasingly younger and active clientele. However, knowledge about joint forces during sports is scarce and often only estimated. As skiing is controversially debated as an activity following THA, we measured joint loads in instrumented THAs during cross-country ski simulation. Five untrained subjects who had previously received instrumented THAs were instructed to perform double poling and diagonal poling exercises on a ski simulator and to walk on a treadmill at 4 km/h as a reference exercise. The joint contact force, bending moment, and torsion torque on the implant were determined. Time-load patterns were generated. Loading peaks were compared intra-and inter-individually to walking. Statistical parameter mapping was used to visualise significant differences between exercises across the movement cycle. Loading maxima were mostly lower or adjacent to loading maxima of walking, except for diagonal poling with foot lift. Differences in execution of double poling resulted in different time-load patterns of torsion torque. Diagonal bending moments exceeded walking bending moments slightly. Outliers were observed. Double or diagonal poling can be safely practiced by THA patients on a ski simulator in the late postoperative period due to mostly lower or adjacent loading forces to walking. Unilateral standing phases should be minimized. Patient's experience and bone quality affect recommendation of this sport. Limitations concern limited generalizability of small cohort and simulated environment.

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined through radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r2=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r2=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment.

An exotendon—a spring that couples the legs when attached to a runner’s shoes—reduces the energetic cost of running, but the effects on joint contact forces are unknown. This study examined whether running with an exotendon alters the forces in the hip, knee and ankle. We used muscle-driven simulations of experimental data to compute compressive and shear contact forces at the hip, knee, and ankle joints for seven participants running at 2.7 m/s with and without an exotendon. We found that runners using the exotendon experienced a 8.4% reduction in peak knee compressive contact force (1.0 ± 0.7 BW; P = 0.026), and no change in the peak knee shear contact force. The primary contributor to this reduction was lower forces in the quadriceps muscles, which decreased their contribution to peak knee compressive contact force by 12.2% (−0.8 ± 0.7 BW; P = 0.018). We observed no change in the peak compressive or shear contact forces in the hip or ankle joints. Though the exotendon was not originally designed to reduce joint forces, our findings highlight the ability of this simple device to make changes to gait that reduce both energetic cost and compressive knee force.

Hip adduction moment (HAM) is commonly used as a surrogate for hip joint loading; however, its validity across different gait tasks and modifications remains unclear. Understanding how gait modification influences this relationship is essential for developing effective load-management strategies for individuals with or at risk of hip osteoarthritis. This study examined the relationship between HAM and hip joint reaction force (HJRF) during walking and running under natural and foot progression modification conditions in healthy adults. Musculoskeletal modelling in OpenSim was used to estimate HJRF, and inverse dynamics were applied to calculate HAM. Spearman’s correlation coefficients were used to assess the relationship between HAM and HJRF across gait conditions. Paired t-tests and linear mixed models, accounting for speed where applicable, assessed differences between natural and modified gait. During walking, early stance HAM was strongly correlated with HJRF in both natural (ρ = 0.923, p < 0.001) and toe-in conditions (ρ = 0.851, p < 0.001). Toe-in walking significantly reduced HAM (p = 0.017) and HJRF (p = 0.037) compared to natural walking. During running, peak HAM had lower but significant correlation with HJRF in the natural condition (ρ = 0.703, p < 0.001), but no significant association was observed during toe-out running (p = 0.065). Toe-out running significantly decreased HAM (p = 0.006) while HJRF remained unchanged (p = 0.941). Gait modification influences the coupling between HAM and HJRF, particularly during dynamic tasks such as running. While HAM is a valid indicator of hip loading during walking, it becomes less representative under altered dynamic conditions. These findings highlight the limitations of using single-plane moments as a surrogate for joint loading.

Joint contact and muscle forces estimated with musculoskeletal modeling techniques offer useful metrics describing movement quality that benefit multiple research and clinical applications. The expensive processing of laboratory data associated with generating these outputs presents challenges to researchers and clinicians, including significant time and expertise requirements that limit the number of subjects typically evaluated. The objective of the current study was to develop and compare machine learning techniques for rapid, data-driven estimation of musculoskeletal metrics from derived gait lab data. OpenSim estimates of patient joint and muscle forces during activities of daily living were simulated using laboratory data from 70 total knee replacement patients and used to develop 4 different machine learning algorithms. Trained machine learning models predicted both trend and magnitude of estimated joint contact (mean correlation coefficients ranging from 0.93 to 0.94 during gait) and muscle forces (mean correlation coefficients ranging from 0.83 to 0.91 during gait) based on anthropometrics, ground reaction forces, and joint angle data. Patient mechanics were accurately predicted by recurrent neural networks, even after removing dependence on key subsets of predictor features. The ability to quickly estimate patient mechanics from derived measurements of movement has the potential to broaden the impact of musculoskeletal modeling by enabling faster assessment in both clinical and research settings.

Gait biomechanics and daily steps are important aspects of knee-joint loading that change after anterior cruciate ligament reconstruction (ACLR). Understanding their relationship during the first 6 months post-ACLR could help clinicians develop comprehensive rehabilitation interventions that promote optimal joint loading after injury, thereby improving long-term knee-joint health. To compare biomechanical gait waveforms throughout stance at early time points post-ACLR in individuals with different daily step behaviors at 6 months post-ACLR and to examine how these gait waveforms compare with those of uninjured controls. Case-control study. Laboratory. A total of 32 individuals with primary ACLR assigned to the low-step group (LSG; n = 13) or the high-step group (HSG; n = 19) based on their average daily steps at 6 months post-ACLR and 32 uninjured matched controls. Gait biomechanics were collected at 2, 4, and 6 months post-ACLR for the ACLR groups and at a single session for the control group. Knee-adduction moment, knee-extension moment (KEM), and knee-flexion angle (KFA) waveforms were calculated during gait stance and then compared via functional waveform analyses. Mean differences and corresponding 95% CIs between groups were reported. Primary results demonstrated less KFA (1%-45% versus 79%-92% of stance) and greater KEM (65%-93% of stance) at 2 months and greater knee-adduction moment (14%-20% versus 68%-92% of stance) at 4 months post-ACLR for the HSG compared with the LSG. Knee-adduction moment, KEM, and KFA waveforms differed across various proportions of stance at all time points between the step and control groups. Differences in gait biomechanics were present at 2 and 4 months post-ACLR between step groups, with the LSG demonstrating an overall more flexed knee and more profound stepwise underloading throughout stance than the HSG. The results indicate a relation between early gait biomechanics and later daily step behaviors post-ACLR.

Cartilage homeostasis is governed by articular chondrocytes via their ability to modulate extracellular matrix production and degradation. In turn, chondrocyte activity is regulated by growth factors such as those of the transforming growth factor β (TGFβ) family. Members of this family include the TGFβs, bone morphogenetic proteins (BMPs), and growth and differentiation factors (GDFs). Signaling by this protein family uniquely activates SMAD-dependent signaling and transcription but also activates SMAD-independent signaling via MAPKs such as ERK and TAK1. This review will address the pivotal role of the TGFβ family in cartilage biology by listing several TGFβ family members and describing their signaling and importance for cartilage maintenance. In addition, it is discussed how (pathological) processes such as aging, mechanical stress, and inflammation contribute to altered TGFβ family signaling, leading to disturbed cartilage metabolism and disease.

Stair walking is more demanding than level walking, and differences have been found between steady-state stair walking and gait-to-stair or stair-to-gait transition. However, there is limited knowledge on steady-state stair walking biomechanics in people with hip osteoarthritis (HOA) as all existing data were obtained during gait-to-stair transition. The aim of the present study was to investigate the effects of mild-to-moderate HOA on hip and trunk biomechanics and dynamic balance during steady-state stair walking. Hip and trunk biomechanics and dynamic balance during steady-state stair walking were assessed in 21 participants with mild-to-moderate HOA and 21 age-matched healthy controls using an optoelectronic motion capture system and a custom-built instrumented six-step staircase. Dynamic balance was assessed using the inverted pendulum model with an extrapolated centre of mass. Differences between the two groups were analysed with an independent t-test either on discrete parameters or on entire time curves using statistical parametric mapping. The HOA group showed longer stride and stance phase durations during stair ascent and descent, and lower peak vertical CoM acceleration during stair descent vs. the control group. Trunk kinematics did not differ between groups. Lower frontal plane hip range of motion and hip internal rotation moment, but greater anterior margin of stability were observed during stair ascent in the HOA vs. control group. Mild-to-moderate HOA reduced frontal hip mobility but did not affect mediolateral dynamic balance during steady-state stair walking. Despite a lack of alterations in sagittal hip or trunk kinematics or dynamics, greater anterior margin of stability in HOA vs. control participants showed a more stable but potentially less efficient motion during stair ascent. Lastly, lower vertical acceleration during stair descent might reduce impact and joint loading at initial contact. Future studies should analyse gait efficiency and joint loading, and the effect of HOA severity and muscle force capacity on steady-state stair walking biomechanics in people with HOA.

People with knee osteoarthritis who adopt a modified foot progression angle (FPA) during gait often benefit from a reduction in the knee adduction moment. It is unknown, however, whether changes in the FPA increase hip moments, a surrogate measure of hip loading, which will increase the mechanical demand on the joint. This study examined how altering the FPA affects hip moments. Individuals with knee osteoarthritis walked on an instrumented treadmill with their baseline gait, 10° toe-in gait, and 10° toe-out gait. A musculoskeletal modeling package was used to compute joint moments from the experimental data. Fifty participants were selected from a larger study who reduced their peak knee adduction moment with a modified FPA. In this group, participants reduced the first peak of the knee adduction moment by 7.6% with 10° toe-in gait and reduced the second peak by 11.0% with 10° toe-out gait. Modifying the FPA reduced the early-stance hip abduction moment, at the time of peak hip contact force, by 4.3% ± 1.3% for 10° toe-in gait (p = 0.005, d = 0.49) and by 4.6% ± 1.1% for 10° toe-out gait (p < 0.001, d = 0.59) without increasing the flexion and internal rotation moments (p > 0.15). Additionally, 74% of individuals reduced their total hip moment at time of peak hip contact force with a modified FPA. In summary, when adopting a FPA modification that reduced the knee adduction moment, participants, on average, did not increase surrogate measures of hip loading.

Research concerning forefoot strike pattern (FFS) versus rearfoot strike pattern (RFS) running has focused on the ground reaction force even though internal joint contact forces are a more direct measure of the loads responsible for injury. The main purpose of this study was to determine the internal loading of the joints for each strike pattern. A secondary purpose was to determine if converted FFS and RFS runners can adequately represent habitual runners with regards to the internal joint loading. Using inverse dynamics to calculate the net joint moments and reaction forces and optimization techniques to estimate muscle forces, we determined the axial compressive loading at the ankle, knee, and hip. Subjects consisted of 15 habitual FFS and 15 habitual RFS competitive runners. Each subject ran at a preferred running velocity with their habitual strike pattern and then converted to the opposite strike pattern. Plantar flexor muscle forces and net ankle joint moments were greater in the FFS running compared to the RFS running during the first half of the stance phase. The average contact forces during this period increased by 41.7% at the ankle and 14.4% at the knee joint during FFS running. Peak ankle joint contact force was 1.5 body weights greater during FFS running (p<0.05). There was no evidence to support a difference between habitual and converted running for joint contact forces. The increased loading at the ankle joint for FFS is an area of concern for individuals considering altering their foot strike pattern.