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Abstract Background Direct skeletal fixation, a surgical technique enabling the attachment of an external prosthesis directly to the bone through a percutaneous implant, offers an enticing solution for patients with lower limb amputations facing socket-related issues. However, understanding of its impact on musculoskeletal function remains limited. Methods This study compares pre- and 1-year post-osseointegration surgery outcomes, focusing on patient-reported measures and musculoskeletal system function during level-ground walking. Two participants with unilateral transfemoral amputations and two participants with bilateral transfemoral amputations completed the questionnaire for transfemoral amputations (Q-TFA) and underwent gait analysis. Musculoskeletal modelling simulations were conducted. Results Results showed improved Q-TFA scores for all participants. Participants showed reduced amputated limb peak hip extension angles, flexion torques and contact forces at the push-off phase of the gait cycle. Post-operatively, hip adduction angles and abduction moments increased, indicating more natural gait patterns. Whilst one participant demonstrated increased post-operative walking speed, others walked more slowly. Conclusions The study revealed diverse adaptation patterns after one year in individuals with transfemoral amputations transitioning to bone-anchored prostheses. Additional longer-term data is necessary to enable generalization and clinical implications of these results.

Background: Direct skeletal fixation, a surgical technique enabling the attachment of an external prosthesis directly to the bone through a percutaneous implant, offers an enticing solution for patients with lower limb amputations facing socket-related issues. However, understanding of its impact on musculoskeletal function remains limited. Methods: This study compares pre- and 1-year post-osseointegration surgery outcomes, focusing on patient-reported measures and musculoskeletal system function during level-ground walking. Two participants with unilateral transfemoral amputations and two participants with bilateral transfemoral amputations completed the questionnaire for transfemoral amputations (Q-TFA) and underwent gait analysis. Musculoskeletal modelling simulations were conducted. Results: Results showed improved Q-TFA scores for all participants. Participants showed reduced amputated limb peak hip extension angles, flexion torques and contact forces at the push-off phase of the gait cycle. Post-operatively, hip adduction angles and abduction moments increased, indicating more natural gait patterns. Whilst one participant demonstrated increased post-operative walking speed, others walked more slowly. Conclusions: The study revealed diverse adaptation patterns after one year in individuals with transfemoral amputations transitioning to bone-anchored prostheses. Additional longer-term data is necessary to enable generalization and clinical implications of these results. [ABSTRACT FROM AUTHOR]

Musculoskeletal modeling is a cost-effective way to design and test wearable robots, ensuring maximum efficiency for individuals. This article explores the simulation of exoskeletons to support the lower limbs and reduce the metabolic cost of walking. The exoskeleton consists of a flexible joint as an actuator made up of four elastomers that store the negative power of the knee joint during the walking cycle as energy, and release it to assist the wearer in the next phase of walking. The Computed Muscle Control (CMC) algorithm in OpenSim is used to find joint torque, total metabolic savings, and the resulting changes in muscle activity. Subsequently, the behavior of implementing the passive exoskeleton is evaluated and the results are compared to a semi-active robot on lower body limbs. The study concluded that while the passive robot exerts extra force on the hamstring muscles in the first half of the swing phase and increases the torque applied to the knee joint. It decreases the activity of the quadriceps muscles in the second half. To compensate for this problem exoskeletons are commonly equipped with a motor. However, this article's findings suggest that utilizing the motorized robot, while decreasing the torque in the targeted joint, actually boosts the performance of surrounding muscles and consumes more metabolic energy than in a passive state. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the consistency of musculoskeletal modelling outcomes during walking in chronic post-stroke patients, focusing on both affected and unaffected sides. Understanding the specific muscle forces involved is crucial for designing targeted rehabilitation strategies to improve balance and mobility after a stroke. Musculoskeletal modelling provides valuable insights into muscle and joint loading, aiding clinicians in analysing essential biomarkers and enhancing patients’ functional outcomes. However, the repeatability of these modelling outcomes in stroke gait has not been thoroughly explored until now. Twelve post-stroke, hemiparetic survivors were included in the study, which consisted of a gait analysis protocol to capture kinematic and kinetic variables. Two generic full body MSK models—Hamner (Ham) and Rajagopal (Raj)—were used to compute joint angles and muscle forces during walking, with combinations of two muscle force estimation algorithms (Static Optimisation (SO) and Computed Muscle Control (CMC)) and different joint degrees-of-freedoms (DOF). The multiple correlation coefficient (MCCoef) was used to compute repeatability for all forces, grouped based on anatomical function. Regardless of models and DOFs, the mean minimum (0.75) and maximum (0.94) MCCoefs denote moderate-to-excellent repeatability for all muscle groups. The combination of the Ham model and SO provided the most repeatable muscle force estimations of all the muscle groups except for the hip flexors, adductors and internal rotators. DOF configuration did not generally affect muscle force repeatability in the Ham–SO case, although the 311 seemed to relate to the highest values. Lastly, the DOF setting had a significant effect on some muscle groups’ force output, with the highest magnitudes reported for the 321 and 322 of non-paretic and paretic hip adductors and extensors, knee flexors and ankle dorsiflexors and paretic knee flexors. The primary findings of our study can assist users in selecting the most suitable modelling workflow and encourage the widespread adoption of MSK modelling in clinical practice.

The musculotendon mechanics of the hamstrings during high-speed running are thought to relate to injury but have rarely been examined in the context of prospectively occurring injury. This prospective study describes the hamstring musculotendon mechanics of two elite rugby players who sustained hamstring injuries during on-field running. Athletes undertook biomechanical analyses of high-speed running during a Super Rugby pre-season, prior to sustaining hamstring injuries during the subsequent competition season. The biceps femoris long head muscle experienced the greatest strain of all hamstring muscles during the late swing phase. When expressed relative to force capacity, biceps femoris long head also experienced the greatest musculotendon forces of all hamstring muscles. Musculotendon strain and force may both be key mechanisms for hamstring injury during the late swing phase of running. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the consistency of musculoskeletal modelling outcomes during walking in chronic post-stroke patients, focusing on both affected and unaffected sides. Understanding the specific muscle forces involved is crucial for designing targeted rehabilitation strategies to improve balance and mobility after a stroke. Musculoskeletal modelling provides valuable insights into muscle and joint loading, aiding clinicians in analysing essential biomarkers and enhancing patients' functional outcomes. However, the repeatability of these modelling outcomes in stroke gait has not been thoroughly explored until now. Twelve post-stroke, hemiparetic survivors were included in the study, which consisted of a gait analysis protocol to capture kinematic and kinetic variables. Two generic full body MSK models—Hamner (Ham) and Rajagopal (Raj)—were used to compute joint angles and muscle forces during walking, with combinations of two muscle force estimation algorithms (Static Optimisation (SO) and Computed Muscle Control (CMC)) and different joint degrees-of-freedoms (DOF). The multiple correlation coefficient (MCCoef) was used to compute repeatability for all forces, grouped based on anatomical function. Regardless of models and DOFs, the mean minimum (0.75) and maximum (0.94) MCCoefs denote moderate-to-excellent repeatability for all muscle groups. The combination of the Ham model and SO provided the most repeatable muscle force estimations of all the muscle groups except for the hip flexors, adductors and internal rotators. DOF configuration did not generally affect muscle force repeatability in the Ham–SO case, although the 311 seemed to relate to the highest values. Lastly, the DOF setting had a significant effect on some muscle groups' force output, with the highest magnitudes reported for the 321 and 322 of non-paretic and paretic hip adductors and extensors, knee flexors and ankle dorsiflexors and paretic knee flexors. The primary findings of our study can assist users in selecting the most suitable modelling workflow and encourage the widespread adoption of MSK modelling in clinical practice. [ABSTRACT FROM AUTHOR]

Individuals with transfemoral lower limb amputations walk with adapted gait. These kinetic and kinematic compensatory strategies will manifest as differences in muscle recruitment patterns. It is important to characterize these differences to understand the reduced endurance, reduced functionality, and progression of co-morbidities in this population. This study aims to characterize muscle recruitment during gait of highly functional individuals with traumatic transfemoral amputations donning state-of-the-art prosthetics compared to able-bodied controls. Inverse dynamic and static optimisation methods of musculoskeletal modelling were used to quantify muscle forces of the residual and intact limb over a gait cycle for 11 individuals with traumatic transfemoral amputation and for 11 able-bodied controls. Estimates of peak muscle activation and impulse were calculated to assess contraction intensity and energy expenditure. The generalized estimation equation method was used to compare the maximum values of force, peak activation, and impulse of the major muscles. The force exhibited by the residual limb’s iliacus, psoas major, adductor longus, tensor fasciae latae and pectineus is significantly higher than the forces in these muscles of the intact contralateral limb group and the able-bodied control group (p < 0.001). These muscles appear to be recruited for their flexor moment arm, indicative of the increased demand due to the loss of the plantar flexors. The major hip extensors are recruited to a lesser degree in the residual limb group compared to the intact limb group (p < 0.001). The plantar flexors of the intact limb appear to compensate for the amputated limb with significantly higher forces compared to the able-bodied controls (p = 0.01). Significant differences found in impulse and peak activation consisted of higher values for the limbs (residual and/or intact) of individuals with transfemoral lower limb amputations compared to the able-bodied controls, demonstrating an elevated cost of gait. This study highlights asymmetry in hip muscle recruitment between the residual and the intact limb of individuals with transfemoral lower limb amputations. Overall elevated impulse and peak activation in the limbs of individuals with transfemoral amputation, compared to able-bodied controls, may manifest in the reduced walking endurance of this population. This demand should be minimised in rehabilitation protocols.

Introduction & Purpose Bones adapt its shape and strength in response to mechanical loading. Tissue-level mechanical stresses, i.e., hydrostatic compressive stress and octahedral shear stress, regulate biological events on the cellular and molecular level, and thereby impact tissue histomorphology and changes in bony geometry (Carter & Beaupré, 2007). Mechanobiological multi-scale simulations based on gait analysis data, musculoskeletal (MSK) modelling and finite element (FE) analysis enable to estimate tissue-level bone loads and predict growth patterns (Shefelbine & Carter, 2004). Such simulations have the potential to inform clinical decision-making in patients with pathological bone deformations, e.g. increased femoral anteversion angle (AVA), which are common in children with cerebral palsy (CP). However, the time-consuming process of creating subject-specific models has previously restricted studies to small sample sizes (n = 1-4 participants), thereby limiting the generalizability of findings (Carriero et al., 2011; Yadav et al., 2021). Moreover, the simulations have not been validated directly due to a lack of longitudinal experimental data, which hinders the widespread use and implementation in clinical settings. Over the last years, we focused our research efforts to overcome these hurdles. We developed a workflow to streamline the process to create subject-specific FE model (Koller et al., 2023). In this study we aimed to use this workflow and 1) analyze growth patterns in a comparable large sample of typically developing (TD) children and children with CP and 2) validate the growth predictions, i.e. compare predicted with measured bone growth. Methods Magnetic resonance images (MRI) and three-dimensional motion capture data including marker trajectories and ground reaction forces of 13 TD children (10 ± 2.2 years old, mass: 36.8 ± 9.5 kg) and 12 children with CP (10.4 ± 3.8 years old, mass: 30.1 ± 10.8 kg) were analyzed for this study. All participants walked without walking aids and with a self-selected speed. Details of the data collection are described in previous publications (Kainz et al., 2017; Koller et al., 2023). From 10 TD children we collected the MRI and motion capture data twice with approximately two years between occasions. MRI images were used to create subject-specific MSK models (Veerkamp et al., 2021) based on an OpenSim model (Kaneda et al., 2023), which allows to estimate medial and lateral knee joint contact forces (JCF) as well as the patellofemoral JCF. Each participant’s model and the corresponding gait analysis data were used to calculate joint angles, muscle forces and JCFs using inverse kinematics, static optimization and joint reaction load analyses with OpenSim 4.2, respectively. For each participant, muscle forces and JCF of two representative steps (left and right) were chosen as loading condition for the FE simulations and each side was analyzed separately. Each femur was segmented using 3D Slicer and the geometry was used to calculate the bending of the femoral shaft. Our previously developed tool was used to create subject-specific hexahedral meshes with several layers of elements aligned with the growth plates (Koller et al., 2023). Nine load instances were selected based on the JCF peaks and the valley in-between during the stance phase. JCFs and muscle forces (n = 26) acting on the femur at these timepoints were used as loading conditions for FE analysis. Linear elastic material properties were assigned to the different parts of the femur and FEBio3 was used to calculate principal stresses within the growth plates. The growth rate due to mechanical loading was estimated as the osteogenic index (OI), which was calculated based on the hydrostatic compressive stress and octahedral shear stress for each element within the growth plates (Stevens et al., 1999; Yadav et al., 2021). Positive and negative OI values indicate regions where growth is likely to be promoted or inhibited, respectively. Image comparison methods were employed to identify variability between OIs (Bradski, 2000). The knee flexion angle alters the orientation of knee JCFs in respect to the distal growth plate resulting in different induced stress regimes. Hence, we divided the children with CP in two groups: one with normal knee flexion angles (n = 15 femurs, CPnormal) and one with increased knee flexion (n = 8 femurs, CPhigh_knee_flexion) during the stance phase. For aim 1, we compared the femoral geometry and OI between CP groups and the TD children. For aim 2 (validation), growth predictions were performed for all femurs where data of two occasions was available (n = 20 femurs). Monte-Carlo-analysis (n = 1,320 for each femur) were performed to estimate which mechanobiological model parameters lead to the most realistic simulations. Linear regression analyses were used to identify whether measured development of AVA can be predicted by the mechanobiological multi-scale simulations. Results The bending of the femoral shaft was significantly different between all groups (Figure 1B). The representative reference OI distribution from the TD femurs showed a ring-shape at the proximal growth plate. Within the CP cohort, image comparison revealed higher inter-subject variability (p < 0.001) whereas some participants show ring-shape distribution similar to the TD cohort and others linear-gradient shapes with high values on the lateral side of the growth plate. At the distal growth plate, OI distribution for TD femurs showed highest values in the posterior notch region and on the medial-anterior edge. The OI distribution of the CPnormal group had its peak values in similar areas as the TD group but with additional peaks at the anterior-lateral edge. The OI distribution generated from the CPhigh_knee_flexion group showed a linear gradient from high to low values from anterior to posterior side (Figure 1D). Between data collection sessions, TD children grew 13.5 ± 3.3 cm and gained 8.2 ± 3.2 kg of body mass during the two years. Participants’ AVA changed between -13.1° and 11.8° (mean: -1.3 ± 5.8°) between sessions. Analysis of kinematics, muscle and JCFs did not show differences between those experiencing an increase of AVA to those that showed a decrease. Multi-scale predictions and measurements of AVA development showed significant linear correlation (p < 0.001) with an explanatory power of R2 = 0.5 (Figure 1C). Discussion At the distal growth plate, the OI distribution showed more growth in the anterior compared to the posterior region in the CPhigh_knee_flexion compared to the CPnormal and TD groups. Progressive promoted growth in the anterior compartment over a longer period could lead to higher anterior bending of the femoral shaft. Indeed, our geometrical analysis revealed a more bended femoral shaft in the CPhigh_knee_flexion group compared to other groups. The variability of the OI at the proximal growth plate within the CP cohort was higher compared to the TD group indicating that some CP participants are likely to experience normal growth whereas in others, the proximal femur will develop pathologically. This agrees with clinical observation where some children with CP develop deformities while others don’t. Despite the fact that no significant differences were found in joint kinematics, femoral loading and growth plate orientation between TD children with different growth patterns, multi-scale simulations were sensitive enough to identify differences and predict AVA development with reasonable accuracy. Conclusion Femoral growth is influenced by a complex interplay between gait pattern, femoral morphology and internal loading on a tissue-level. Our results showed that multi-scale simulations are able to discriminate between different growth patterns and predict growth trends in agreement with experimental observations. In order to increase our confidence in the simulations and pave the road to in-silico informed clinical decision-making in the near future, longitudinal simulation studies including a larger sample size and individuals with pathological growth are needed to be conducted. References Bradski, G. (2000). The OpenCV library. Dr. Dobb’s Journal of Software Tools. Carriero, A., Jonkers, I., & Shefelbine, S. J. (2011). Mechanobiological prediction of proximal femoral deformities in children with cerebral palsy. Computer Methods in Biomechanics and Biomedical Engineering, 14(3), 253–262. https://doi.org/10.1080/10255841003682505 Carter, D. R., & Beaupré, G. S. (2007). Skeletal function and form: Mechanobiology of skeletal development, aging, and regeneration. Cambridge University Press. Kainz, H., Hoang, H. X., Stockton, C., Boyd, R. R., Lloyd, D. G., & Carty, C. P. (2017). Accuracy and reliability of marker-based approaches to scale the pelvis, thigh, and shank segments in musculoskeletal models. Journal of Applied Biomechanics, 33(5), 354–360. https://doi.org/10.1123/jab.2016-0282 Kaneda, J. M., Seagers, K. A., Uhlrich, S. D., Kolesar, J. A., Thomas, K. A., & Delp, S. L. (2023). Can static optimization detect changes in peak medial knee contact forces induced by gait modifications? Journal of Biomechanics, 152, Article 111569. https://doi.org/10.1016/j.jbiomech.2023.111569 Koller, W., Gonçalves, B., Baca, A., & Kainz, H. (2023). Intra- and inter-subject variability of femoral growth plate stresses in typically developing children and children with cerebral palsy. Frontiers in Bioengineering and Biotechnology, 11, Article 1140527. https://doi.org/10.3389/fbioe.2023.1140527 Shefelbine, S. J., & Carter, D. R. (2004). Mechanobiological predictions of femoral anteversion in cerebral palsy. Annals of Biomedical Engineering, 32(2), 297–305. https://doi.org/10.1023/B:ABME.0000012750.73170.ba Stevens, S. S., Beaupré, G. S., & Carter, D. R. (1999). Computer model of endochondral growth and ossification in long bones: Biological and mechanobiological influences. Journal of Orthopaedic Research, 17(5), 646–653. https://doi.org/10.1002/jor.1100170505 Veerkamp, K., Kainz, H., Killen, B. A., Jónasdóttir, H., & van der Krogt, M. M. (2021). Torsion Tool: An automated tool for personalising femoral and tibial geometries in OpenSim musculoskeletal models. Journal of Biomechanics, 125, Article 110589. https://doi.org/10.1016/j.jbiomech.2021.110589 Yadav, P., Fernández, M. P., & Gutierrez-Farewik, E. M. (2021). Influence of loading direction due to physical activity on proximal femoral growth tendency. Medical Engineering & Physics, 90, 83-91. https://doi.org/10.1016/j.medengphy.2021.02.008

The objectives of this study were to analyse the peak muscle-tendon (MT) strain of the hamstring during an entire acceleration sprint overground and examine their relationship with relative joint angles and segment orientation in the sagittal plane, which are the direct causes of MT strain. Kinematic data were recorded using a 3D inertial motion capture system in 21 male semi-professional soccer players during 40-metre overground sprint. Scaled musculoskeletal models were used to estimate peak MT strain in the hamstring over 16 steps. Biceps femoris long head (BFLH) exhibited the largest peaks in MT strain compared to semitendinosus (ST) and semimembranosus (SM) muscles across all the steps, with its overall strain decreased as the number of steps and maximum speed increased. Hip flexion angle was found to be a strong predictor (p < 0.001) of joint angles, being the orientation of the pelvis in the sagittal plane of the segment with the greatest influence (p < 0.001) on the peak MT strain of BFLH during sprinting. The current study provides a biomechanical explanation for the high proportion of hamstring injuries in the acceleration phase of sprinting. [ABSTRACT FROM AUTHOR]

Augmentative exoskeletons (AEs) are wearable orthotic devices that, when coupled with a healthy individual, can significantly enhance endurance, speed, and strength. Exoskeletons are function-specific and individual-specific, with a multitude of possible configurations and joint mechanisms. This complexity presents a challenging scenario to quantitatively determine the optimal choice of the kinematic configuration of the exoskeleton for the intended activity. A comprehensive simulation-based framework for obtaining an optimal configuration of a passive augmentative exoskeleton for backpack load carriage during walking is the theme of this research paper. A musculoskeletal-based simulation approach on 16 possible kinematic configurations with different Degrees of Freedom (DoF) at the exoskeleton structure's hip, knee, and ankle joints was performed, and a configuration with three DoF at the hip, one DoF at the knee, three DoF at the ankle was quantitatively chosen. The Root Mean Square of Deviations (RMSD) and Maximum Deviations (MaxDev) between the kinematically coupled human–exoskeleton system were used as criteria along with the Cumulative Weight Score (CWS). The chosen configuration from the simulation was designed, realised, and experimentally validated. The error of the joint angles between the simulation and experiments with the chosen configuration was less than 3° at the hip and ankle joints and less than 6° at the knee joints. [ABSTRACT FROM AUTHOR]

Through predictive simulations, multibody models can aid the treatment of spinal pathologies by identifying optimal surgical procedures. Critical to achieving accurate predictions is the definition of the intervertebral joint. The joint pose is often defined by virtual palpation. Intervertebral joint stiffnesses are either derived from literature, or specimen-specific stiffnesses are calculated with optimisation methods. This study tested the feasibility of an optimisation method for determining the specimen-specific stiffnesses and investigated the influence of the assigned joint pose on the subject-specific estimated stiffness. Furthermore, the influence of the joint pose and the stiffness on the accuracy of the predicted motion was investigated. A computed tomography based model of a lumbar spine segment was created. Joints were defined from virtually palpated landmarks sampled with a Latin Hypercube technique from a possible Cartesian space. An optimisation method was used to determine specimen-specific stiffnesses for 500 models. A two-factor analysis was performed by running forward dynamic simulations for ten different stiffnesses for each successfully optimised model. The optimisations calculated a large range of stiffnesses, indicating the optimised specimen-specific stiffnesses were highly sensitive to the assigned joint pose and related uncertainties. A limited number of combinations of optimised joint stiffnesses and joint poses could accurately predict the kinematics. The two-factor analysis indicated that, for the ranges explored, the joint pose definition was more important than the stiffness. To obtain kinematic prediction errors below 1 mm and 1° and suitable specimen-specific stiffnesses the precision of virtually palpated landmarks for joint definition should be better than 2.9 mm.

Using synchronous kinematic and kinetic data in simulations of human running typically leads to dynamic inconsistencies. Minimizing residual forces and moments is subsequently important to ensure plausible model outputs. A variety of approaches suitable for residual reduction are available in OpenSim; however, a detailed comparison is yet to be conducted. This study compared OpenSim tools applicable for residual reduction in simulations of human running. Multiple approaches (i.e. Residual Reduction Algorithm, MocoTrack, AddBiomechanics) designed to reduce residual forces and moments were examined using an existing dataset of treadmill running at 5.0 ms−1. The computational time, residual forces and moments, and joint kinematics and kinetics from each approach were compared. A computational cost to residual reduction trade-off was identified, where lower residuals were achieved using approaches with longer computational times. The AddBiomechanics and MocoTrack approaches produced variable lower and upper body kinematics, respectively, versus the remaining approaches. Joint kinetics were similar between approaches; however, MocoTrack generated noisier upper limb joint torque signals. MocoTrack was the best-performing approach for reducing residuals to near-zero levels, at the cost of longer computational times. This study provides OpenSim users with evidence to inform decision-making at the residual reduction step of their workflow.

Background: Given the inherent variability in walking speeds encountered in day-to-day activities, understanding the corresponding alterations in ankle biomechanics would provide valuable clinical insights. Therefore, the objective of this study was to examine the influence of different walking speeds on biomechanical parameters, utilizing gait analysis and musculoskeletal modelling.Methods: Twenty healthy volunteers without any lower limb medical history were included in this study. Treadmill-assisted gait-analysis with walking speeds of 0.8 m/s and 1.1 m/s was performed using the Gait Real-time Analysis Interactive Lab (GRAIL®). Collected kinematic data and ground reaction forces were processed via the AnyBody® modeling system to determine ankle kinetics and muscle forces of the lower leg. Data were statistically analyzed using statistical parametric mapping to reveal both spatiotemporal and magnitude significant differences.Results: Significant differences were found for both magnitude and spatiotemporal curves between 0.8 m/s and 1.1 m/s for the ankle flexion (p < 0.001), subtalar force (p < 0.001), ankle joint reaction force and muscles forces of the M. gastrocnemius, M. soleus and M. peroneus longus (α = 0.05). No significant spatiotemporal differences were found between 0.8 m/s and 1.1 m/s for the M. tibialis anterior and posterior.Discussion: A significant impact on ankle joint kinematics and kinetics was observed when comparing walking speeds of 0.8 m/s and 1.1 m/s. The findings of this study underscore the influence of walking speed on the biomechanics of the ankle. Such insights may provide a biomechanical rationale for several therapeutic and preventative strategies for ankle conditions.

Introduction: Spaceflight is associated with substantial and variable musculoskeletal (MSK) adaptations. Characterisation of muscle and joint loading profiles can provide key information to better align exercise prescription to astronaut MSK adaptations upon return-to-Earth. A case-study is presented of single-leg hopping in hypogravity to demonstrate the additional benefit computational MSK modelling has when estimating lower-limb MSK loading. Methods: A single male participant performed single-leg vertical hopping whilst attached to a body weight support system to replicate five gravity conditions (0.17, 0.25, 0.37, 0.50, 1 g). Experimental joint kinematics, joint kinetics and ground reaction forces were tracked in a data-tracking direct collocation simulation framework. Ground reaction forces, sagittal plane hip, knee and ankle net joint moments, quadriceps muscle forces (Rectus Femoris and three Vasti muscles), and hip, knee and ankle joint reaction forces were extracted for analysis. Estimated quadriceps muscle forces were input into a muscle adaptation model to predict a meaningful increase in muscle cross-sectional area, defined in (DeFreitas et al., 2011). Results: Two distinct strategies were observed to cope with the increase in ground reaction forces as gravity increased. Hypogravity was associated with an ankle dominant strategy with increased range of motion and net plantarflexor moment that was not seen at the hip or knee, and the Rectus Femoris being the primary contributor to quadriceps muscle force. At 1 g, all three joints had increased range of motion and net extensor moments relative to 0.50 g, with the Vasti muscles becoming the main muscles contributing to quadriceps muscle force. Additionally, hip joint reaction force did not increase substantially as gravity increased, whereas the other two joints increased monotonically with gravity. The predicted volume of exercise needed to counteract muscle adaptations decreased substantially with gravity. Despite the ankle dominant strategy in hypogravity, the loading on the knee muscles and joint also increased, demonstrating this provided more information about MSK loading. Discussion: This approach, supplemented with muscle-adaptation models, can be used to compare MSK loading between exercises to enhance astronaut exercise prescription. [ABSTRACT FROM AUTHOR]

Abstract Background Balance control is important for mobility, yet exoskeleton research has mainly focused on improving metabolic energy efficiency. Here we present a biomimetic exoskeleton controller that supports walking balance and reduces muscle activity. Methods Humans restore balance after a perturbation by adjusting activity of the muscles actuating the ankle in proportion to deviations from steady-state center of mass kinematics. We designed a controller that mimics the neural control of steady-state walking and the balance recovery responses to perturbations. This controller uses both feedback from ankle kinematics in accordance with an existing model and feedback from the center of mass velocity. Control parameters were estimated by fitting the experimental relation between kinematics and ankle moments observed in humans that were walking while being perturbed by push and pull perturbations. This identified model was implemented on a bilateral ankle exoskeleton. Results Across twelve subjects, exoskeleton support reduced calf muscle activity in steady-state walking by 19% with respect to a minimal impedance controller (p

Introduction: Spaceflight is associated with substantial and variable musculoskeletal (MSK) adaptations. Characterisation of muscle and joint loading profiles can provide key information to better align exercise prescription to astronaut MSK adaptations upon return-to-Earth. A case-study is presented of single-leg hopping in hypogravity to demonstrate the additional benefit computational MSK modelling has when estimating lower-limb MSK loading. Methods: A single male participant performed single-leg vertical hopping whilst attached to a body weight support system to replicate five gravity conditions (0.17, 0.25, 0.37, 0.50, 1 g). Experimental joint kinematics, joint kinetics and ground reaction forces were tracked in a data-tracking direct collocation simulation framework. Ground reaction forces, sagittal plane hip, knee and ankle net joint moments, quadriceps muscle forces (Rectus Femoris and three Vasti muscles), and hip, knee and ankle joint reaction forces were extracted for analysis. Estimated quadriceps muscle forces were input into a muscle adaptation model to predict a meaningful increase in muscle cross-sectional area, defined in (DeFreitas et al., 2011). Results: Two distinct strategies were observed to cope with the increase in ground reaction forces as gravity increased. Hypogravity was associated with an ankle dominant strategy with increased range of motion and net plantarflexor moment that was not seen at the hip or knee, and the Rectus Femoris being the primary contributor to quadriceps muscle force. At 1 g, all three joints had increased range of motion and net extensor moments relative to 0.50 g, with the Vasti muscles becoming the main muscles contributing to quadriceps muscle force. Additionally, hip joint reaction force did not increase substantially as gravity increased, whereas the other two joints increased monotonically with gravity. The predicted volume of exercise needed to counteract muscle adaptations decreased substantially with gravity. Despite the ankle dominant strategy in hypogravity, the loading on the knee muscles and joint also increased, demonstrating this provided more information about MSK loading. Discussion: This approach, supplemented with muscle-adaptation models, can be used to compare MSK loading between exercises to enhance astronaut exercise prescription.

Introduction: Musculoskeletal multibody models of the spine can be used to investigate the biomechanical behaviour of the spine. In this context, a correct characterisation of the passive mechanical properties of the intervertebral joint is crucial. The intervertebral joint stiffness, in particular, is typically derived from the literature, and the differences between individuals and spine levels are often disregarded.Methods: This study tested if an optimisation method of personalising the intervertebral joint stiffnesses was able to capture expected stiffness variation between specimens and between spine levels and if the variation between spine levels could be accurately captured using a generic scaling ratio. Multibody models of six T12 to sacrum spine specimens were created from computed tomography data. For each specimen, two models were created: one with uniform stiffnesses across spine levels, and one accounting for level dependency. Three loading conditions were simulated. The initial stiffness values were optimised to minimize the kinematic error.Results: There was a range of optimised stiffnesses across the specimens and the models with level dependent stiffnesses were less accurate than the models without. Using an optimised stiffness substantially reduced prediction errors.Discussion: The optimisation captured the expected variation between specimens, and the prediction errors demonstrated the importance of accounting for level dependency. The inaccuracy of the predicted kinematics for the level-dependent models indicated that a generic scaling ratio is not a suitable method to account for the level dependency. The variation in the optimised stiffnesses for the different loading conditions indicates personalised stiffnesses should also be considered load-specific.

Musculoskeletal models have been widely used for detailed biomechanical analysis to characterise various functional impairments given their ability to estimate movement variables (i.e., muscle forces and joint moments) which cannot be readily measured in vivo. Physics-based computational neuromusculoskeletal models can interpret the dynamic interaction between neural drive to muscles, muscle dynamics, body and joint kinematics and kinetics. Still, such set of solutions suffers from slowness, especially for the complex models, hindering the utility in real-time applications. In recent years, data-driven methods have emerged as a promising alternative due to the benefits in speedy and simple implementation, but they cannot reflect the underlying neuromechanical processes. This paper proposes a physics-informed deep learning framework for musculoskeletal modelling, where physics-based domain knowledge is brought into the data-driven model as soft constraints to penalise/regularise the data-driven model. We use the synchronous muscle forces and joint kinematics prediction from surface electromyogram (sEMG) as the exemplar to illustrate the proposed framework. Convolutional neural network (CNN) is employed as the deep neural network to implement the proposed framework. Simultaneously, the physics law between muscle forces and joint kinematics is used the soft constraint. Experimental validations on two groups of data, including one benchmark dataset and one self-collected dataset from six healthy subjects, are performed. The experimental results demonstrate the effectiveness and robustness of the proposed framework.

Background. Architectural properties of the muscles are the prime predictors of functional attributes and force-generating capacity of the muscles. This data is vital for musculoskeletal modelling and selecting the appropriate muscle–tendon units for tendon transfers. Cadaveric data for architectural properties is the gold standard and primary input for musculoskeletal modelling. There is a paucity of these datasets, especially in the leg muscles. Methods. Sixty muscles of the anterior and lateral compartments from twelve formalin-fixed lower limbs were studied for gross architecture, including the peculiar fibre arrangements and architectural properties of muscles. Muscle weight, muscle length, fibre length, pennation angle and sarcomere length were measured. Normalised fibre length, fibre length to muscle length ratio (FL/ML ratio), and the physiological cross-sectional area (PCSA) were calculated from the obtained data. Results. Muscles displayed a combination of architectural strategies and were partly fusiform and partly pennate. The tibialis anterior and peroneus longus were the heaviest muscles in their respective compartments and showed more extensive origin from the nearby deep facial sheets. Long fibre length and less pennation angle were seen in muscles of the extensor compartment. Potential muscle power was highest in the tibialis anterior and peroneus longus and least in the extensor hallucis longus. Conclusions. Arching of the foot and eversion are peculiar to humans and recent in evolution. Due to the functional demand of maintaining the medial longitudinal arch and eversion, the tibialis anterior and peroneus longus have more muscle weight and larger physiological cross-sectional area and are potentially more powerful. Extensor compartment muscles were architecturally more suited for excursions because of the long fibre length and less pennation angle. This study contributes baseline normative data for musculoskeletal modelling platforms and simulation tools – an emerging area in biomechanics and tendon transfers.

Featured Application: Awareness of the role of the extensor digitorum longus can point to rehabilitation treatment and functional surgery towards more effective solutions. Equinus and equinovarus foot deviations (EVFD) are the most frequent lower limb acquired deformities in stroke survivors. We analysed the contribution that the tibialis anterior (TA), extensor digitorum longus (EDL) and plantarflexor muscles play in EVFD via a biomechanical musculoskeletal model of the ankle–foot complex. Our model was composed of 28 bones (connected by either revolute joints or bone surface contacts), 15 ligaments (modelled as non-linear springs), and 10 muscles, modelled as force actuators. Different combinations of muscle contractions were also simulated. Our results demonstrate that, compared to the condition when the foot is suspended off the ground, the contraction of the TA alone produces dorsiflexion (from −18° to 0°) and a greater supination/inversion (from 12° to 30°). The EDL alone produces dorsiflexion (from −18° to −6°), forefoot pronation (25°) and calcaneal eversion (5.6°). Only TA and EDL synergistic action can lead the foot to dorsiflexion suitable for most daily life activities (≥20°) without any deviation in the frontal plane. When pathological contractures of the plantarflexor muscles were simulated, foot deformities reproducing EVFD were obtained. These results can be relevant for clinical applications, highlighting the importance of EDL assessment, which may help to design appropriate functional surgery and plan targeted rehabilitation treatments. [ABSTRACT FROM AUTHOR]

Background: Balance control is important for mobility, yet exoskeleton research has mainly focused on improving metabolic energy efficiency. Here we present a biomimetic exoskeleton controller that supports walking balance and reduces muscle activity. Methods: Humans restore balance after a perturbation by adjusting activity of the muscles actuating the ankle in proportion to deviations from steady-state center of mass kinematics. We designed a controller that mimics the neural control of steady-state walking and the balance recovery responses to perturbations. This controller uses both feedback from ankle kinematics in accordance with an existing model and feedback from the center of mass velocity. Control parameters were estimated by fitting the experimental relation between kinematics and ankle moments observed in humans that were walking while being perturbed by push and pull perturbations. This identified model was implemented on a bilateral ankle exoskeleton. Results: Across twelve subjects, exoskeleton support reduced calf muscle activity in steady-state walking by 19% with respect to a minimal impedance controller (p < 0.001). Proportional feedback of the center of mass velocity improved balance support after perturbation. Muscle activity is reduced in response to push and pull perturbations by 10% (p = 0.006) and 16% (p < 0.001) and center of mass deviations by 9% (p = 0.026) and 18% (p = 0.002) with respect to the same controller without center of mass feedback. Conclusion: Our control approach implemented on bilateral ankle exoskeletons can thus effectively support steady-state walking and balance control and therefore has the potential to improve mobility in balance-impaired individuals. [ABSTRACT FROM AUTHOR]

Purpose: Inverse-dynamics (ID) analysis is an approach widely used for studying spine biomechanics and the estimation of muscle forces. Despite the increasing structural complexity of spine models, ID analysis results substantially rely on accurate kinematic data that most of the current technologies are not capable to provide. For this reason, the model complexity is drastically reduced by assuming three degrees of freedom spherical joints and generic kinematic coupling constraints. Moreover, the majority of current ID spine models neglect the contribution of passive structures. The aim of this ID analysis study was to determine the impact of modelled passive structures (i.e., ligaments and intervertebral discs) on remaining joint forces and torques that muscles must balance in the functional spinal unit. Methods: For this purpose, an existing generic spine model developed for the use in the demoa software environment was transferred into the musculoskeletal modelling platform OpenSim. The thoracolumbar spine model previously used in forward-dynamics (FD) simulations provided a full kinematic description of a flexion-extension movement. By using the obtained in silico kinematics, ID analysis was performed. The individual contribution of passive elements to the generalised net joint forces and torques was evaluated in a step-wise approach increasing the model complexity by adding individual biological structures of the spine. Results: The implementation of intervertebral discs and ligaments has significantly reduced compressive loading and anterior torque that is attributed to the acting net muscle forces by −200% and −75%, respectively. The ID model kinematics and kinetics were cross-validated against the FD simulation results. Conclusion: This study clearly shows the importance of incorporating passive spinal structures on the accurate computation of remaining joint loads. Furthermore, for the first time, a generic spine model was used and cross-validated in two different musculoskeletal modelling platforms, i.e., demoa and OpenSim, respectively. In future, a comparison of neuromuscular control strategies for spinal movement can be investigated using both approaches. [ABSTRACT FROM AUTHOR]

The ankle joint is one of the most involved joints in uphill walking. Furthermore, it is well known that toe walking increases the external dorsiflexion moment in the first half of stance during level walking. However, the effects of different foot-strike patterns on plantar flexor muscle forces, ankle joint forces, and other lower limb joint and muscle forces are unknown. Do foot-strike patterns during 18° uphill walking affect lower limb sagittal joint angles and moments, as well as joint contact and muscle forces? This study was based on a data subset from previous publications, analysing uphill walking on an 18° ramp at a preset speed of 1.1 m/s in 18 male participants (34 limbs analyzed, 27 ± 5 years). Participants were divided into two groups based on their foot-strike pattern at initial contact: heel (HC) and forefoot (FC). Lower limb sagittal joint angles and moments as well as joint contact and muscle forces were assessed. Differences between the groups were assessed using two-sample t-tests. FC showed increased soleus and gastrocnemius muscle forces as well as ankle joint forces during loading response and mid stance compared to HC. The soleus muscle force impulse was 51.1% higher in the FC group than in the HC group (p < 0.001). On the other hand, FC had a lower absolute centre of mass vertical displacement and reduced knee and hip joint, as well as iliopsoas and hamstring muscle force impulses. In terms of plantar flexor and ankle joint loading, it is advantageous to exhibit a heel strike pattern. The current results can be used to recommend foot-strike patterns for uphill walking, particularly in the presence or prevention of musculoskeletal issues. • A heel strike pattern reduces ankle joint forces and plantar flexor muscle forces. • A forefoot strike pattern leads to reduced knee and hip joint force impulses. • A forefoot strike pattern has lower iliopsoas and hamstrings force impulses. [ABSTRACT FROM AUTHOR]

Augmentative exoskeletons (AEs) are wearable orthotic devices that, when coupled with a healthy individual, can significantly enhance endurance, speed, and strength. Exoskeletons are function-specific and individual-specific, with a multitude of possible configurations and joint mechanisms. This complexity presents a challenging scenario to quantitatively determine the optimal choice of the kinematic configuration of the exoskeleton for the intended activity. A comprehensive simulation-based framework for obtaining an optimal configuration of a passive augmentative exoskeleton for backpack load carriage during walking is the theme of this research paper. A musculoskeletal-based simulation approach on 16 possible kinematic configurations with different Degrees of Freedom (DoF) at the exoskeleton structure’s hip, knee, and ankle joints was performed, and a configuration with three DoF at the hip, one DoF at the knee, three DoF at the ankle was quantitatively chosen. The Root Mean Square of Deviations (RMSD) and Maximum Deviations (MaxDev) between the kinematically coupled human–exoskeleton system were used as criteria along with the Cumulative Weight Score (CWS). The chosen configuration from the simulation was designed, realised, and experimentally validated. The error of the joint angles between the simulation and experiments with the chosen configuration was less than 3° at the hip and ankle joints and less than 6° at the knee joints.

Alterations in joint contact forces (JCFs) are thought to be important mechanisms for the onset and progression of many musculoskeletal and orthopaedic pain disorders. Computational approaches to JCFs assessment represent the only non-invasive means of estimating in-vivo forces; but this cannot be undertaken in free-living environments. Here, we used deep neural networks to train models to predict JCFs, using only joint angles as predictors. Our neural network models were generally able to predict JCFs with errors within published minimal detectable change values. The errors ranged from the lowest value of 0.03 bodyweight (BW) (ankle medial-lateral JCF in walking) to a maximum of 0.65BW (knee VT JCF in running). Interestingly, we also found that over parametrised neural networks by training on longer epochs (>100) resulted in better and smoother waveform predictions. Our methods for predicting JCFs using only joint kinematics hold a lot of promise in allowing clinicians and coaches to continuously monitor tissue loading in free-living environments.

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Joint moment measurements represent an objective biomechemical parameter in joint health assessment. Inverse dynamics based on 3D motion capture data is the current 'gold standard’ to estimate joint moments. Recently, machine learning combined with data measured by wearable technologies such electromyography (EMG), inertial measurement units (IMU), and electrogoniometers (GON) has been used to enable fast, easy, and low-cost measurements of joint moments. This study investigates the ability of various deep neural networks to predict lower limb joint moments merely from IMU sensors. The performance of five different deep neural networks (InceptionTimePlus, eXplainable convolutional neural network (XCM), XCMplus, Recurrent neural network (RNNplus), and Time Series Transformer (TSTPlus)) were tested to predict hip, knee, ankle, and subtalar moments using acceleration and gyroscope measurements of four IMU sensors at the trunk, thigh, shank, and foot. Multiple locomotion modes were considered including level-ground walking, treadmill walking, stair ascent, stair descent, ramp ascent, and ramp descent. We show that XCM can accurately predict lower limb joint moments using data of only four IMUs with RMSE of 0.046 ± 0.013 Nm/kg compared to 0.064 ± 0.003 Nm/kg on average for the other architectures. We found that hip, knee, and ankle joint moments predictions had a comparable RMSE with an average of 0.069 Nm/kg, while subtalar joint moments had the lowest RMSE of 0.033 Nm/kg. The real-time feedback that can be derived from the proposed method can be highly valuable for sports scientists and physiotherapists to gain insights into biomechanics, technique, and form to develop personalized training and rehabilitation programs.

Marker-based Optical Motion Capture (OMC) systems and associated musculoskeletal (MSK) modelling predictions offer non-invasively obtainable insights into muscle and joint loading at an in vivo level, aiding clinical decision-making. However, an OMC system is lab-based, expensive, and requires a line of sight. Inertial Motion Capture (IMC) techniques are widely-used alternatives, which are portable, user-friendly, and relatively low-cost, although with lesser accuracy. Irrespective of the choice of motion capture technique, one typically uses an MSK model to obtain the kinematic and kinetic outputs, which is a computationally expensive tool increasingly well approximated by machine learning (ML) methods. Here, an ML approach is presented that maps experimentally recorded IMC input data to the human upper-extremity MSK model outputs computed from ('gold standard') OMC input data. Essentially, this proof-of-concept study aims to predict higher-quality MSK outputs from the much easier-to-obtain IMC data. We use OMC and IMC data simultaneously collected for the same subjects to train different ML architectures that predict OMC-driven MSK outputs from IMC measurements. In particular, we employed various neural network (NN) architectures, such as Feed-Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs) (vanilla, Long Short-Term Memory, and Gated Recurrent Unit) and a comprehensive search for the best-fit model in the hyperparameters space in both subject-exposed (SE) as well as subject-naive (SN) settings. We observed a comparable performance for both FFNN and RNN models, which have a high degree of agreement (r avg , SE , FFNN = 0.90 ± 0.19 , r avg , SE , RNN = 0.89 ± 0.17 , r avg , SN , FFNN = 0.84 ± 0.23 , and r avg , SN , RNN = 0.78 ± 0.23 ) with the desired OMC-driven MSK estimates for held-out test data. The findings demonstrate that mapping IMC inputs to OMC-driven MSK outputs using ML models could be instrumental in transitioning MSK modelling from 'lab to field'. [ABSTRACT FROM AUTHOR]

This simulation study aimed to explore the effects of mass and mass distribution of powered ankle–foot orthoses, on net joint moments and individual muscle forces throughout the lower limb. Using OpenSim inverse kinematics, dynamics, and static optimization tools, the gait cycles of ten subjects were analyzed. The biomechanical models of these subjects were appended with ideal powered ankle–foot orthoses of different masses and actuator positions, as to determine the effect that these design factors had on the subject's kinetics during normal walking. It was found that when the mass of the device was distributed more distally and posteriorly on the leg, both the net joint moments and overall lower limb muscle forces were more negatively impacted. However, individual muscle forces were found to have varying results which were attributed to the flow-on effect of the orthosis, the antagonistic pairing of muscles, and how the activity of individual muscles affect each other. It was found that mass and mass distribution of powered ankle–foot orthoses could be optimized as to more accurately mimic natural kinetics, reducing net joint moments and overall muscle forces of the lower limb, and must consider individual muscles as to reduce potentially detrimental muscle fatigue or muscular disuse. OpenSim modelling method to explore the effect of mass and mass distribution on muscle forces and joint moments, showing potential mass positioning and the effects of these positions, mass, and actuation on the muscle force integral. [ABSTRACT FROM AUTHOR]

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context. [ABSTRACT FROM AUTHOR]

In spine research, two possibilities to generate models exist: generic (population-based) models representing the average human and subject-specific representations of individuals. Despite the increasing interest in subject specificity, individualisation of spine models remains challenging. Neuro-musculoskeletal (NMS) models enable the analysis and prediction of dynamic motions by incorporating active muscles attaching to bones that are connected using articulating joints under the assumption of rigid body dynamics. In this study, we used forward-dynamic simulations to compare a generic NMS multibody model of the thoracolumbar spine including fully articulated vertebrae, detailed musculature, passive ligaments and linear intervertebral disc (IVD) models with an individualised model to assess the contribution of individual biological structures. Individualisation was achieved by integrating skeletal geometry from computed tomography and custom-selected muscle and ligament paths. Both models underwent a gravitational settling process and a forward flexion-to-extension movement. The model-specific load distribution in an equilibrated upright position and local stiffness in the L4/5 functional spinal unit (FSU) is compared. Load sharing between occurring internal forces generated by individual biological structures and their contribution to the FSU stiffness was computed. The main finding of our simulations is an apparent shift in load sharing with individualisation from an equally distributed element contribution of IVD, ligaments and muscles in the generic spine model to a predominant muscle contribution in the individualised model depending on the analysed spine level. [ABSTRACT FROM AUTHOR]

Local botulinum toxin (BTX-A, Botox®) injection in overactive muscles is a standard treatment in patients with cerebral palsy. The effect is markedly reduced in children above the age of 6 to 7. One possible reason for this is the muscle volume affected by the drug. Nine patients (aged 11.5; 8.7–14.5 years) with cerebral palsy GMFCS I were treated with BTX-A for equinus gait at the gastrocnemii and soleus muscles. BTX-A was administered at one or two injection sites per muscle belly and with a maximum of 50 U per injection site. Physical examination, instrumented gait analysis, and musculoskeletal modelling were used to assess standard muscle parameters, kinematics, and kinetics during gait. Magnetic resonance imaging (MRI) was used to detect the affected muscle volume. All the measurements were carried out pre-, 6 weeks post-, and 12 weeks post-BTX-A. Between 9 and 15% of the muscle volume was affected by BTX-A. There was no effect on gait kinematics and kinetics after BTX-A injection, indicating that the overall kinetic demand placed on the plantar flexor muscles remained unchanged. BTX-A is an effective drug for inducing muscle weakness. However, in our patient cohort, the volume of the affected muscle section was limited, and the remaining non-affected parts were able to compensate for the weakened part of the muscle by taking over the kinetic demands associated with gait, thus not enabling a net functional effect in older children. We recommend distributing the drug over the whole muscle belly through multiple injection sites. [ABSTRACT FROM AUTHOR]

Featured Application: Quasi-static finite element model to adjust the stiffness of 3D-printed insoles during walking for patients with diabetic foot by using ankle moments and joint reaction forces as efficient boundary conditions. Diabetes-adapted insoles are essential in prevention and rehabilitation of foot ulcers in diabetic foot syndrome. However, their manufacture is labour-intensive and costly. Therefore, the study aims to present an alternative method that allows the individual adjustment of the stiffness of the insoles using the finite element (FE) method and subsequent 3D printing. In the study, 3D gait analysis followed by musculoskeletal modelling was used to determine the boundary conditions of a healthy subject for the FE model. While muscle forces are elaborately implemented in most studies, this FE model presented a more efficient way by using ankle moments and joint reaction forces. The deviation between the simulated plantar peak pressure and the experimentally determined using the Pedar system amounted to 234 kPa in the heel area and 30 kPa in the toe area. The stiffness of the individual insole was adjusted by applying soft insole plugs in areas where high plantar pressures occurred during walking. Three different Young's moduli were analysed in these areas (0.5 MPa, 1.0 MPa, 1.5 MPa). The computer-based approach to adjust the stiffness of an individual insole revealed a plantar peak pressure reduction by 37% in the heel area and by 119% in the toe area with a Young's modulus of 0.5 MPa. The presented method could be a valuable tool in the cost-efficient development and engineering of subject-specific 3D-printed insoles for patients with diabetic foot syndrome. [ABSTRACT FROM AUTHOR]

• PS group had greater forward lean which reduced hip flexion on the operated limb. • MBS and PS groups favoured their non-operated limb during sit-to-stand tasks. • Operated limb had less muscle and knee contact forces compared to non-operated limb. • TKA groups had reduced medial compartment knee contact force during sit-to-stand tasks. • Control group favoured their dominant limb during sit-to-stand tasks. Understanding how forces are transmitted through the knee after TKA is essential, as it may explain why many patients experience pain or functional limitations during various activities. This study compared knee muscle forces and knee contact forces (KCF) during sit-to-stand in patients one year after unilateral total knee arthroplasty (TKA) with either a medial ball-and-socket (MBS) or posterior stabilized (PS) implant and compared them to a group of similarly healthy aged controls (CTRL). A musculoskeletal model and static optimization estimated lower limb kinematics, knee kinetics, muscle forces, and KCFs. The normalized sit-to-stand cycle was compared among the groups using statistical nonparametric mapping, and peak between-limb differences were compared using discrete statistics. The PS group required greater forward lean during the sit-to-stand task, causing greater spine flexion, posterior pelvic tilt, and decreased hip flexion on the operated limb. PS and MBS groups favoured their non-operated limb, resulting in less range of motion throughout the lower limb, lower knee kinetics, muscle forces, and KCFs on the operated limb. Compared to the controls, the MBS and PS groups had reduced medial compartment KCF. The control group did favour their dominant limb over their non-dominant limb. Post-operative rehabilitation should continue to promote greater use of the operated knee to have more symmetrical loading between operated and non-operated limbs and improve strength and mobility at the hip and ankle joints. One year after surgery, TKA patients remain with reduced muscle forces and KCF on their operated limb during a sit-to-stand task, regardless whether they received an MBS or PS implant. [ABSTRACT FROM AUTHOR]

Low back pain is the most prevalent and disabling condition worldwide, with a high recurrence rate in the general adult population. A set of open-sourced trunk musculoskeletal models was used to investigate trunk flexion kinematics under different motor control strategies, including minimizing shearing or compressive loads at the L4/L5 or L5/S1 level. A control strategy that minimizes the load on the lower lumbar intervertebral disc can result in two kinematic patterns—the "restricted lumbar spine" and the "overflexed lumbar spine"—in performing the trunk flexion task. The "restricted" pattern can reduce the overall load on the lower lumbar levels, whereas the "overflexed" pattern can reduce the shearing force only at the L4/L5 level and increase the compressive and shearing forces at the L5/S1 level and the compressive force at the L4/L5 level. This study investigated the relationships between specific trunk kinematics in patients with low back pain and lumbar intervertebral loading via musculoskeletal modelling and simulation. The results provide insight into individualized treatment for patients with low back pain. • Study provides insights to help those with low back pain lower lumbar load and pain. • Reducing lumbar flexion during tasks lessens lower back loads, lowering injury risk. • The "overflexed" strategy may raise spinal load at L5/S1, speeding up disc degeneration. [ABSTRACT FROM AUTHOR]