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Accurate predictions of joint contact forces through computer simulation of musculoskeletal dynamics can provide insight, in a non-invasive manner, into the joint loads of patients with osteoarthritis and healthy controls. The current approach to assume optimal control, in terms of metabolic energy expenditure, remains a major limitation of the prediction of muscle activation patterns that determine joint contact forces. Stochastically optimal muscle control, in the form of a stochastic component superimposed to the optimal control, could potentially explain the inter-trial variability as observed in measured knee contact forces during level walking. A probabilistic approach was used to predict sets of possible muscle activation patterns within a 5 and 10% limit from the optimal muscle activation pattern. The knee contact forces determined by both the optimal and stochastically optimal muscle activation patterns were compared to the corresponding knee contact force patterns measured by an instrumented implant. The range of muscle control patterns captured the inter-trial variability of knee contact forces for most of the gait cycle, suggesting that the probabilistic approach used here is representative of a stochastically optimal control that accounts for co-contraction, whereas during some time intervals a more explicit representation of the motor control strategy is required. These findings underline the importance of stochastically optimal muscle control in the prediction of knee forces within a multi-body dynamics approach. [ABSTRACT FROM AUTHOR]

This article applies methods typically used in engineering applications to the optimization of human locomotion, more specifically a swimmer's underwater 'dolphin kick'. This is a dual-objective problem which seeks the optimal trade-off between thrust (simulated using Lighthill's fish propulsion method) and the force in the muscles to produce this thrust (simulated using musculoskeletal modelling). The expense of the analyses leads to the use of a surrogate modelling based optimization technique (multi-objective expected improvement using Kriging). The results indicate that optimal human motion does in many respects follow that of fish, with low frequency eel-like techniques suitable for endurance and a high frequency tuna-like kick for high thrust. The MATLAB® code, including thrust and muscle activity models, is made available in an online repository. [ABSTRACT FROM AUTHOR]

Knee functional disorders are one of the most common lower extremity non-traumatic injuries reported by cyclists. Incorrect bicycle configuration may predispose cyclist to injury but the evidence of an effect of saddle setback on knee pain remains inconclusive. The aim of this study was to determine the effect of saddle setback on knee joint forces during pedalling using a musculoskeletal modelling approach. Ten cyclists were assessed under three saddle setback conditions (range of changes in saddle position ~6 cm) while pedalling at a steady power output of 200 W and cadence of 90 rpm. A cycling musculoskeletal model was developed and knee joint forces were estimated using an inverse dynamics method associated with a static optimisation procedure. Our results indicate that moving the saddle forwards was not associated with an increase of patellofemoral joint forces. On the contrary, the tibiofemoral mean and peak compression force were 14 and 15% higher in the Backward than in the Forward condition, respectively. The peak compression force was related to neither pedal force nor quadriceps muscle force but coincided with the eccentric contraction of knee flexor muscles. These findings should benefit bike fitting practitioners and coaches in the design of specific training/rehabilitation protocols. [ABSTRACT FROM AUTHOR]

• Transfemoral amputees adopt compensatory strategies during walking. • Intact limb hip muscles have critical roles on mediolateral balance. • The prosthesis provides prominent support, progression and breaking during stance. • Increased pelvis tilt towards residual limb was associated with reduced hip motion. Individuals with unilateral transfemoral amputation depend on compensatory muscle and joint function to generate motion of the lower limbs, which can produce gait asymmetry; however, the functional role of the intact and residual limb muscles of transfemoral amputees in generating progression, support, and mediolateral balance of the body during walking is not well understood. The aim of this study was to quantify the contributions of the intact and the residual limb's contralateral muscles to body center of mass (COM) acceleration during walking in transfemoral amputees. Three-dimensional subject-specific musculoskeletal models of 6 transfemoral amputees fitted with a socket-type prosthesis were developed and used to quantify muscle forces and muscle contributions to the fore-aft, vertical, and mediolateral body COM acceleration using a pseudo-inverse ground reaction force decomposition method during over-ground walking. Anterior pelvic tilt and hip range of motion in the sagittal and frontal planes of the intact limb was significantly larger than those in the residual limb (p <0.05). The mean contributions of the intact limb hip muscles to body COM support, forward propulsion and mediolateral balance were significantly greater than those in the residual limb (p <0.05). Gluteus maximus contributed more to propulsion and support, while gluteus medius contributed more to balance than other muscles in the intact limb than the residual limb. The findings demonstrate the role of the intact limb hip musculature in compensating for reduced or absent muscles and joint function in the residual limb of transfemoral amputees during walking. The results may be useful in developing rehabilitation programs and design of prostheses to improve gait symmetry and mitigate post-operative musculoskeletal pathology. [ABSTRACT FROM AUTHOR]

Background: Bone shapes strongly influence force and moment predictions of kinematic and musculoskeletal models used in motion analysis. The precise determination of joint reference frames is essential for accurate predictions. Since clinical motion analysis typically does not include medical imaging, from which bone shapes may be obtained, scaling methods using reference subjects to create subject-specific bone geometries are widely used.Research Question: This study investigated if lower limb bone shape predictions from skin-based measurements, utilising an underlying statistical shape model (SSM) that corrects for soft tissue artefacts in digitisation, can be used to improve conventional linear scaling methods of bone geometries.Methods: SSMs created from 35 healthy adult femurs and tibiae/fibulae were used to reconstruct bone shapes by minimising the distance between anatomical landmarks on the models and those digitised in the motion laboratory or on medical images. Soft tissue artefacts were quantified from magnetic resonance images and then used to predict distances between landmarks digitised on the skin surface and bone. Reconstruction results were compared to linearly scaled models by measuring root mean squared distances to segmented surfaces, calculating differences of commonly used anatomical measures and the errors in the prediction of the hip joint centre.Results: SSM reconstructed surface predictions from varying landmark sets from skin and bone landmarks were more accurate compared to linear scaling methods (2.60-2.95 mm vs. 3.66-3.87 mm median error; p < 0.05). No significant differences were found between SSM reconstructions from bony landmarks and SSM reconstructions from digitised landmarks obtained in the motion lab and therefore reconstructions using skin landmarks are as accurate as reconstructions from landmarks obtained from medical images.Significance: These results indicate that SSM reconstructions can be used to increase the accuracy in obtaining bone shapes from surface digitised experimental data acquired in motion lab environments. [ABSTRACT FROM AUTHOR]

Mechanical devices are common treating methods for knee osteoarthritis. It has the purpose of reducing the internal joint forces and unloading the damaged structure. The reduction is often achieved by alterations in the frontal plan, shifting the contact force from one compartment to the other, leaving the total compressive force unchanged. The aim of this study was to investigate how internal knee joint forces depend on applied external moments during gait. Musculoskeletal models of the gait of 10 healthy subjects were developed in the AnyBody Modelling System and used to simulate applied joint moments about different axes (load cases), each with the magnitude to compensate the net moment about the respective axis by a specified percentage. For each load case, the total, medial and lateral knee compressive force were computed and compared with a baseline case with no external moments applied. Among the investigated moments, hip flexion-extension, knee flexion-extension and ankle plantarflexion-dorsiflexion moment compensations have the most positive impact on the total knee joint compressive force, and combining the 3, each with a 40% compensation of the muscle moments, reduced the first peak by 23.6%, the second by 30.6% and the impulse by 28.6% with respect to no applied moments.

Abstract Background To ensure an efficient and targeted adaptation with low injury risk during strength exercises, knowledge of the participant specific internal loading conditions is essential. The goal of this study was to calculate the lower limb muscles forces during the strength exercises deadlifts, goodmornings and splits squats by means of musculoskeletal simulation. Methods 11 participants were assessed performing 10 different variations of split squats by varying the step length as well as the maximal frontal tibia angle, and 13 participants were measured performing deadlift and goodmorning exercises. Using individualised musculoskeletal models, forces of the Quadriceps (four parts), Hamstrings (four parts) and m. gluteus maximus (three parts) were computed. Results Deadlifts resulted highest loading for the Quadriceps, especially for the vasti (18–34 N/kg), but not for the rectus femoris (8–10 N/kg), which exhibited its greatest loading during split squats (13–27 N/kg) in the rear limb. Hamstrings were loaded isometrically during goodmornings but dynamically during deadlifts. For the m. gluteus maximus, the highest loading was observed during split squats in the front limb (up to 25 N/kg), while deadlifts produced increasingly, large loading over large ranges of motion in hip and knee. Conclusions Acting muscle forces vary between exercises, execution form and joint angle. For all examined muscles, deadlifts produced considerable loading over large ranges of motion, while split squats seem to be highly dependent upon exercise variation. This study provides key information to design strength-training programs with respect to loading conditions and ranges of motion of lower extremity muscles.

Introduction Musculoskeletal models are important tools for studying movement patterns, tissue loading, and neuromechanics. Personalising bone anatomy within models improves analysis accuracy. Few studies have focused on personalising foot bone anatomy, potentially incorrectly estimating the foot’s contribution to locomotion. Statistical shape models have been created for a subset of foot-ankle bones, but have not been validated. This study aimed to develop and validate statistical shape models of the functional segments in the foot: first metatarsal, midfoot (second-to-fifth metatarsals, cuneiforms, cuboid, and navicular), calcaneus, and talus; then, to assess reconstruction accuracy of these shape models using sparse anatomical data. Methods Magnetic resonance images of 24 individuals feet (age = 28 ± 6 years, 52% female, height = 1.73 ± 0.8 m, mass = 66.6 ± 13.8 kg) were manually segmented to generate three-dimensional point clouds. Point clouds were registered and analysed using principal component analysis. For each bone segment, a statistical shape model and principal components were created, describing population shape variation. Statistical shape models were validated by assessing reconstruction accuracy in a leave-one-out cross validation. Statistical shape models were created by excluding a participant’s bone segment and used to reconstruct that same excluded bone using full segmentations and sparse anatomical data (i.e. three discrete points on each segment), for all combinations in the dataset. Tali were not reconstructed using sparse anatomical data due to a lack of externally accessible landmarks. Reconstruction accuracy was assessed using Jaccard index, root mean square error (mm), and Hausdorff distance (mm). Results Reconstructions generated using full segmentations had mean Jaccard indices between 0.77 ± 0.04 and 0.89 ± 0.02, mean root mean square errors between 0.88 ± 0.19 and 1.17 ± 0.18 mm, and mean Hausdorff distances between 2.99 ± 0.98 mm and 6.63 ± 3.68 mm. Reconstructions generated using sparse anatomical data had mean Jaccard indices between 0.67 ± 0.06 and 0.83 ± 0.05, mean root mean square error between 1.21 ± 0.54 mm and 1.66 ± 0.41 mm, and mean Hausdorff distances between 3.21 ± 0.94 mm and 7.19 ± 3.54 mm. Jaccard index was higher (P < 0.01) and root mean square error was lower (P < 0.01) in reconstructions from full segmentations compared to sparse anatomical data. Hausdorff distance was lower (P < 0.01) for midfoot and calcaneus reconstructions using full segmentations compared to sparse anatomical data. Conclusion For the first time, statistical shape models of the primary functional segments of the foot were developed and validated. Foot segments can be reconstructed with minimal error using full segmentations and sparse anatomical landmarks. In future, larger training datasets could increase statistical shape model robustness, extending use to paediatric or pathological populations.

Medial knee joint osteoarthritis (OA) is a debilitating and prevalent condition. Surgical treatment consists of redistributing the forces from the medial to the lateral compartment through osteotomy, or replacing the joint surfaces. As the mediolateral load distribution is related to the action of the musculature around the knee, the aim of this study was to devise a technique to redistribute these forces non-surgically through changes in muscle excitation. Eight healthy subjects participated in the experiment, and neuromuscular electrical stimulation was used to change the muscle forces around the knee. A musculoskeletal model was used to quantify the loading on the medial compartment of the knee, and a novel algorithm devised and implemented to simulate neuromuscular electrical stimulation. The forces and moments at the knee, ground reaction forces, walking velocity and step length were quantified before and after stimulation. Stimulation of the biceps femoris resulted in a significant decrease in the second peak of the medial knee joint loading by up to 0.17 body weight (p = 0.016). Kinematic parameters were not significantly affected. Neuromuscular electrical stimulation can decrease the peak loads on the medial compartment of the knee, and thus offers a promising therapy for medial knee joint OA.

In this study, a combined subject-specific numerical and experimental investigation was conducted to explore the plantar pressure of an individual. The research utilized finite element (FE) and musculoskeletal modelling based on computed tomography (CT) images of an ankle-foot complex and three-dimensional gait measurements. Muscle forces were estimated using an individualized multi-body musculoskeletal model in five gait phases. The results of the FE model and gait measurements for the same subject revealed the highest stress concentration of 0.48 MPa in the forefoot, which aligns with previously-reported clinical observations. Additionally, the study found that the encapsulated soft tissue FE model with hyper-elastic properties exhibited higher stresses compared to the model with linear-elastic properties, with maximum ratios of 1.16 and 1.88 MPa in the contact pressure and von-Mises stress, respectively. Furthermore, the numerical simulation demonstrated that the use of an individualized insole caused a reduction of 8.3% in the maximum contact plantar pressure and 14.7% in the maximum von-Mises stress in the encapsulated soft tissue. Overall, the developed model in this investigation holds potential for facilitating further studies on foot pathologies and the improvement of rehabilitation techniques in clinical settings., (Creative Commons Attribution license.)

Introduction: Musculoskeletal models are important tools for studying movement patterns, tissue loading, and neuromechanics. Personalising bone anatomy within models improves analysis accuracy. Few studies have focused on personalising foot bone anatomy, potentially incorrectly estimating the foot's contribution to locomotion. Statistical shape models have been created for a subset of foot-ankle bones, but have not been validated. This study aimed to develop and validate statistical shape models of the functional segments in the foot: first metatarsal, midfoot (second-to-fifth metatarsals, cuneiforms, cuboid, and navicular), calcaneus, and talus; then, to assess reconstruction accuracy of these shape models using sparse anatomical data. Methods: Magnetic resonance images of 24 individuals feet (age = 28 ± 6 years, 52% female, height = 1.73 ± 0.8 m, mass = 66.6 ± 13.8 kg) were manually segmented to generate three-dimensional point clouds. Point clouds were registered and analysed using principal component analysis. For each bone segment, a statistical shape model and principal components were created, describing population shape variation. Statistical shape models were validated by assessing reconstruction accuracy in a leave-one-out cross validation. Statistical shape models were created by excluding a participant's bone segment and used to reconstruct that same excluded bone using full segmentations and sparse anatomical data (i.e. three discrete points on each segment), for all combinations in the dataset. Tali were not reconstructed using sparse anatomical data due to a lack of externally accessible landmarks. Reconstruction accuracy was assessed using Jaccard index, root mean square error (mm), and Hausdorff distance (mm). Results: Reconstructions generated using full segmentations had mean Jaccard indices between 0.77 ± 0.04 and 0.89 ± 0.02, mean root mean square errors between 0.88 ± 0.19 and 1.17 ± 0.18 mm, and mean Hausdorff distances between 2.99 ± 0.98 mm and 6.63 ± 3.68 mm. Reconstructions generated using sparse anatomical data had mean Jaccard indices between 0.67 ± 0.06 and 0.83 ± 0.05, mean root mean square error between 1.21 ± 0.54 mm and 1.66 ± 0.41 mm, and mean Hausdorff distances between 3.21 ± 0.94 mm and 7.19 ± 3.54 mm. Jaccard index was higher (P < 0.01) and root mean square error was lower (P < 0.01) in reconstructions from full segmentations compared to sparse anatomical data. Hausdorff distance was lower (P < 0.01) for midfoot and calcaneus reconstructions using full segmentations compared to sparse anatomical data. Conclusion: For the first time, statistical shape models of the primary functional segments of the foot were developed and validated. Foot segments can be reconstructed with minimal error using full segmentations and sparse anatomical landmarks. In future, larger training datasets could increase statistical shape model robustness, extending use to paediatric or pathological populations. [ABSTRACT FROM AUTHOR]

Musculoskeletal models have traditionally relied on measurements of segment kinematics and ground reaction forces and moments (GRF&Ms) from marked-based motion capture and floor-mounted force plates, which are typically limited to laboratory settings. Recent advances in inertial motion capture (IMC) as well as methods for predicting GRF&Ms have enabled the acquisition of these input data in the field. Therefore, this study evaluated the concurrent validity of a novel methodology for estimating the dynamic loading of the lumbar spine during manual materials handling based on a musculoskeletal model driven exclusively using IMC data and predicted GRF&Ms. Trunk kinematics, GRF&Ms, L4–L5 joint reaction forces (JRFs) and erector spinae muscle forces from 13 subjects performing various lifting and transferring tasks were compared to a model driven by simultaneously recorded skin-marker trajectories and force plate data. Moderate to excellent correlations and relatively low magnitude differences were found for the L4–L5 axial compression, erector spinae muscle and vertical ground reaction forces during symmetrical and asymmetrical lifting, but discrepancies were also identified between the models, particularly for the trunk kinematics and L4–L5 shear forces. Based on these results, the presented methodology can be applied for estimating the relative L4–L5 axial compression forces under dynamic conditions during manual materials handling in the field. [ABSTRACT FROM AUTHOR]

• Serratus anterior weakness caused large increases in other muscle activity and joint contact force. • This also disrupted a musculoskeletal model's ability to perform loadsharing optimisation. • Large amounts of Type 2 muscle fibre within serratus anterior hints at role in STS difficulties. • Early signs of weakness could indicate potential difficulties at old age. The ageing population has led to recent increases in musculoskeletal conditions, with muscle weakness a major contributor to functional decline. Understanding the early phases of muscle weakness will help devise treatments to extend musculoskeletal health. Little is understood of the effects of muscle weakness on everyday activities such as sit-to-stand, a determinant of mobility that, in the early stages of weakness, requires upper limb compensation. This experimental and computational modelling study investigated the effects of muscle weakness on upper-extremity muscle forces of 27 healthy adults when using arm rests. Weakness of 29 upper limb muscles was simulated by individually removing each from a musculoskeletal model. Serratus anterior weakness was highlighted as detrimental, with the model unable to fully solve the loadsharing redundancy in its absence, and forces at the elbow and glenohumeral joint and in other muscles were found to be profoundly increased. Its large number of fast-twitch muscle fibres, predisposed to atrophy with age, highlight the centrality of the serratus anterior as a key determinant of mobility in this critical task and a potential source of early immobility through its preferential loss of strength and thus point to the requirement for early clinical interventions to mitigate loss. [ABSTRACT FROM AUTHOR]

The aim of this study was to test the capacity of the force feasible set formalism to predict maximal force exertion during isometric handbraking. Maximal force exertion and upper-limb posture were measured with a force sensor embedded in a handbrake and an optoelectronic system, respectively. Eleven subjects participated in the experiment which consisted of exerting the maximal force in isometric conditions considering five hand brake positions relative to the seat H-point. Then, maximal force was predicted by the force feasible set obtained from an upper-limb musculoskeletal model. The root-mean-square (RMS) of the angle between measured and predicted forces was 8.4° while the RMS error (RMSE) for amplitude prediction was 95.4 N. However, predicted, and measured force amplitudes were highly correlated (r = 0.88, p < 0.05, slope = 0.97, intercept = 73.3N) attesting the capacity of the model to predict force exertion according to the subject's posture. The implications in the framework of ergonomics are then discussed. Practitioner summary: Maximal force exertion is of paramount importance in digital human modelling. We used the force feasible set formalism to predict maximal force exertion during handbraking from posture and anthropometric data. The predicted and measured force orientation showed a RMS of 8.4° while amplitude presented a RMSE of 95.4 N with a strong correlation (r = 0.88, p < 0.05, slope 0.97, intercept 77.3 N). [ABSTRACT FROM AUTHOR]

Juvenile Idiopathic Arthritis (JIA) is a paediatric musculoskeletal disease of unknown aetiology, leading to walking alterations when the lower-limb joints are involved. Diagnosis of JIA is mostly clinical. Imaging can quantify impairments associated to inflammation and joint damage. However, treatment planning could be better supported using dynamic information, such as joint contact forces (JCFs). To this purpose, we used a musculoskeletal model to predict JCFs and investigate how JCFs varied as a result of joint impairment in eighteen children with JIA. Gait analysis data and magnetic resonance images (MRI) were used to develop patient-specific lower-limb musculoskeletal models, which were evaluated for operator-dependent variability (< 3.6°, 0.05 N kg−1 and 0.5 BW for joint angles, moments, and JCFs, respectively). Gait alterations and JCF patterns showed high between-subjects variability reflecting the pathology heterogeneity in the cohort. Higher joint impairment, assessed with MRI-based evaluation, was weakly associated to overall joint overloading. A stronger correlation was observed between impairment of one limb and overload of the contralateral limb, suggesting risky compensatory strategies being adopted, especially at the knee level. This suggests that knee overloading during gait might be a good predictor of disease progression and gait biomechanics should be used to inform treatment planning. [ABSTRACT FROM AUTHOR]

Sprint cycling performance depends upon the balance between muscle and drag forces. This study assessed the influence of upper body position on muscle forces and aerodynamics during seated sprint cycling. Thirteen competitive cyclists attended two sessions. The first session was used to determine handlebar positions to achieve pre-determined hip flexion angles (70–110° in 10° increments) using dynamic bicycle fitting. In the second session, full body kinematics and pedal forces were recorded throughout 2x6-s seated sprints at the pre-determined handlebar positions, and frontal plane images were used to determine the projected frontal area. Leg work, joint work, muscle forces and frontal area were compared at three upper body positions, being optimum (maximum leg work), optimal+10° and optimal-10° of hip flexion. Larger hip (p = 0.01–0.02) and reduced knee (p = 0.02–0.03) contribution to leg work were observed at the optimal+10° position without changes at the ankle joint (p = 0.39). No differences were observed in peak muscle forces across the three body positions (p = 0.06–0.48). Frontal area was reduced at optimum+10° of hip flexion when compared to optimum (p = 0.02) and optimum-10° (p < 0.01). These findings suggest that large changes in upper body position can influence aerodynamics and alter contributions from the knee and hip joints, without influencing peak muscle forces. [ABSTRACT FROM AUTHOR]

This study presents the development of a number of finite element (FE) models of the pelvis using different continuum and structural modelling approaches. Four FE models were developed using different modelling approaches: continuum isotropic, continuum orthotropic, hybrid isotropic and hybrid orthotropic. The models were subjected to an iterative adaptation process based on the Mechanostat principle. Each model was adapted to a number of common daily living activities (walking, stair ascent, stair descent, sit-to-stand and stand-to-sit) by applying onto it joint and muscle loads derived using a musculoskeletal modelling framework. The resulting models, along with a structural model previously developed by the authors, were compared visually in terms of bone architecture, and their response to a single load case was compared to a continuum FE model derived from computed tomography (CT) imaging data. The main findings of this study were that the continuum orthotropic model was the closest to the CT derived model in terms of load response albeit having less total bone volume, suggesting that the role of material directionality in influencing the maximum orthotropic Young's modulus should be included in continuum bone adaptation models. In addition, the hybrid models, where trabecular and cortical bone were distinguished, had similar outcomes, suggesting that the approach to modelling trabecular bone is less influential when the cortex is modelled separately. [ABSTRACT FROM AUTHOR]

Background: Foot pain and deformities are commonly encountered in patients with rheumatoid arthritis (RA). Likewise, Posterior tibial tendon dysfunction (PTTD) is commonly involved in development of foot and ankle abnormalities and has been reported with a prevalence in two-thirds of the RA patients.Research Question: Redundancy in the physiological function between different muscles provides the central nervous system multiple options to perform the same movement but which muscles compensate for the impairment of the tibialis posterior (TP) muscle? And how does these changes affect ankle joint loading?Methods: Experimental and computational disciplines were applied to investigate changes in muscle forces as result of induced pain in the right TP muscle. Twelve healthy subjects were enrolled in the study. Experimental pain was induced in the TP by a single ultrasound graphically guided injection of 1 mL hypertonic saline (5.0% Sodium Chloride). The participants' gait was assessed by skin marker-based motion capture and force plates. Musculoskeletal models were used to investigate compensation mechanisms systematically in the lower under extremity when TP muscle was recruited less as a consequence of the induced pain.Results: Experimental TP muscle pain and simulated reduced strength caused altered muscle recruitment and made the flexor digitorum longus and flexor hallucis longus muscles compensated for the impairment of the TP muscle. Further, the resultant ankle joint force was increased as the strength of the TP muscle was reduced.Significance: The compensation mechanism observed in the present study indicate that alterations in muscle recruitment and muscle force distribution as a result of the underlying disease inflammation itself may contribute to development of chronic foot pain and deformities in patients with RA. Further studies are required to understand the role of PTTD in occurrence of those late adverse musculoskeletal manifestations aiming at search for early preventive strategies. [ABSTRACT FROM AUTHOR]

The Static Optimization (SO) solver in OpenSim estimates muscle activations and forces that only equilibrate applied moments. In this study, SO was enhanced through an open-access MATLAB interface, where calculated muscle activations can additionally satisfy crucial mechanical stability requirements. This Stability-Constrained SO (SCSO) is applicable to many OpenSim models and can potentially produce more biofidelic results than SO alone, especially when antagonistic muscle co-contraction is required to stabilize body joints. This hypothesis was tested using existing models and experimental data in the literature. Muscle activations were calculated by SO and SCSO for a spine model during two series of static trials (i.e. simulation 1 and 2), and also for a lower limb model (supplementary material 2). In simulation 1, symmetric and asymmetric flexion postures were compared, while in simulation 2, various external load heights were compared, where increases in load height did not change the external lumbar flexion moment, but necessitated higher EMG activations. During the tasks in simulation 1, the predicted muscle activations by SCSO demonstrated less average deviation from the EMG data (6.8% −7.5%) compared to those from SO (10.2%). In simulation 2, SO predicts constant muscle activations and forces, while SCSO predicts increases in the average activations of back and abdominal muscles that better match experimental data. Although the SCSO results are sensitive to some parameters (e.g. musculotendon stiffness), when considering the strategy of the central nervous system in distributing muscle forces and in activating antagonistic muscles, the assigned activations by SCSO are more biofidelic than SO. [ABSTRACT FROM AUTHOR]

A novel metric for the validation of musculoskeletal models is proposed, the reachable 3-D workspace (RWS). This new metric was used to compare a generic model scaled in a standard manner to a more subject-specific model. An experimental protocol for assessing the RWS was performed by ten participants for four distinct hand-payload cases. In addition, isometric individual strength measurements were collected for 12 different directions. The strength of subject-specific musculoskeletal models was then computed using the following assumptions: (1) standard routines including the length-mass-fat (LMF) scaling law; (2) the isometric strengths of the muscle elements were optimized to the individual strength measurements using joint strength factors (JSF). The RWS of each participant was subsequently estimated from each of the scaling approaches, LMF and JSF, for the four load cases. The experimental RWS showed that the volume and shape decreased with increasing hand-payload for every participant. The lateral and frontal far-from-torso aspects of the RWS were reduced the most. These trends were reproduced by both strength scaling approaches, but the LMF-scaled models were not able to track the overall RWS volume decrease with increasing payload, since they proved to be weaker than the participants. On the other hand, the optimised JSF subject-specific models performed better on the prediction of the RWS for all payload cases across participants. The RWS can potentially be further used as a subject-specific musculoskeletal model validation, enabling quantification of the volume and shape differences between experimentally and model-predicted RWSs. [ABSTRACT FROM AUTHOR]

Musculoskeletal loading plays an important role in pre-clinical evaluations of hip implants, in particular, bone ingrowth and bone remodelling. Joint force estimation using musculoskeletal models evolved as a viable alternative to in vivo measurement owing to the development of computational resources. This study investigated the efficiencies of four eminent open-source musculoskeletal models in order to determine the model that predicts the most accurate values of hip joint reaction and muscle forces during daily activities. Seven daily living activities of slow walking, normal walking, fast walking, sitting down, standing up, stair down and stair up were simulated in OpenSim using inverse dynamics method. Model predictions of joint kinematics, kinetics and muscle activation patterns were compared with published results. The estimated values of hip joint reaction force were found to corroborate well with in vivo measurements for each activity. Although the estimated values of hip joint reaction force were within a satisfactory range, overestimation of hip joint reaction force (75% BW of measured value) was observed during the late stance phase of walking cycles for all the models. In case of stair up, stair down, standing up and sitting down activities, the error in estimated values of hip joint reaction force were within ~20% BW of the measured value. Based on the results of our study, the London Lower Extremity Model predicted the most accurate value of hip joint reaction force and therefore can be used for applied musculoskeletal loading conditions for numerical investigations on hip implants. [ABSTRACT FROM AUTHOR]

Abstract Surrogate methods for rapid calculation of femoral strain are limited by the scope of the training data. We compared a newly developed training-free method based on the superposition principle (Superposition Principle Method, SPM) and popular surrogate methods for calculating femoral strain during activity. Finite-element calculations of femoral strain, muscle, and joint forces for five different activity types were obtained previously. Multi-linear regression, multivariate adaptive regression splines, and Gaussian process were trained for 50, 100, 200, and 300 random samples generated using Latin Hypercube (LH) and Design of Experiment (DOE) sampling. The SPM method used weighted linear combinations of 173 activity-independent finite-element analyses accounting for each muscle and hip contact force. Across the surrogate methods, we found that 200 DOE samples consistently provided low error (RMSE < 100 µε), with model construction time ranging from 3.8 to 63.3 h and prediction time ranging from 6 to 1236 s per activity. The SPM method provided the lowest error (RMSE = 40 µε), the fastest model construction time (3.2 h) and the second fastest prediction time per activity (36 s) after Multi-linear Regression (6 s). The SPM method will enable large numerical studies of femoral strain and will narrow the gap between bone strain prediction and real-time clinical applications. [ABSTRACT FROM AUTHOR]

Abstract A variety of musculoskeletal models are applied in different modelling environments for estimating muscle forces during gait. Influence of different modelling assumptions and approaches on model outputs are still not fully understood, while direct comparisons of standard approaches have been rarely undertaken. This study seeks to compare joint kinematics, joint kinetics and estimated muscle forces of two standard approaches offered in two different modelling environments (AnyBody, OpenSim). It is hypothesised that distinctive differences exist for individual muscles, while summing up synergists show general agreement. Experimental data of 10 healthy participants (28 ± 5 years, 1.72 ± 0.08 m, 69 ± 12 kg) was used for a standard static optimisation muscle force estimation routine in AnyBody and OpenSim while using two gait-specific musculoskeletal models. Statistical parameter mapping paired t -test was used to compare joint angle, moment and muscle force waveforms in Matlab. Results showed differences especially in sagittal ankle and hip angles as well as sagittal knee moments. Differences were also found for some of the muscles, especially of the triceps surae group and the biceps femoris short head, which occur as a result of different anthropometric and anatomical definitions (mass and inertia of segments, muscle properties) and scaling procedures (static vs. dynamic). Understanding these differences and their cause is crucial to operate such modelling environments in a clinical setting. Future research should focus on alternatives to classical generic musculoskeletal models (e.g. implementation of functional calibration tasks), while using experimental data reflecting normal and pathological gait to gain a better understanding of variations and divergent behaviour between approaches. [ABSTRACT FROM AUTHOR]

Abstract Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p = <0.001) and regression (31.2 ± 15 mm, p = <0.001) methods. The addition of complete pelvis imaging data to the shape modelling workflow further reduced HJC error estimates compared to no imaging (6.6 ± 3.1 mm, p = 0.002). Average RMSE were greatest for the hip flexor and extensor muscle groups using the functional (16.71 mm and 8.87 mm respectively) and regression methods (16.15 mm and 9.97 mm respectively). The effects on moment-arms were less substantial for the shape modelling methods, ranging from 0.05 to 3.2 mm. Shape modelling methods improved HJC location and muscle moment-arm estimates compared to linear scaling of musculoskeletal models in patients with hip osteoarthritis. [ABSTRACT FROM AUTHOR]

Abstract In vivo estimates of tibiotalar and the subtalar joint kinematics can unveil unique information about gait biomechanics, especially in the presence of musculoskeletal disorders affecting the foot and ankle complex. Previous literature investigated the ankle kinematics on ex vivo data sets, but little has been reported for natural walking, and even less for pathological and juvenile populations. This paper proposes an MRI-based morphological fitting methodology for the personalised definition of the tibiotalar and the subtalar joint axes during gait, and investigated its application to characterise the ankle kinematics in twenty patients affected by Juvenile Idiopathic Arthritis (JIA). The estimated joint axes were in line with in vivo and ex vivo literature data and joint kinematics variation subsequent to inter-operator variability was in the order of 1°. The model allowed to investigate, for the first time in patients with JIA, the functional response to joint impairment. The joint kinematics highlighted changes over time that were consistent with changes in the patient's clinical pattern and notably varied from patient to patient. The heterogeneous and patient-specific nature of the effects of JIA was confirmed by the absence of a correlation between a semi-quantitative MRI-based impairment score and a variety of investigated joint kinematics indexes. In conclusion, this study showed the feasibility of using MRI and morphological fitting to identify the tibiotalar and subtalar joint axes in a non-invasive patient-specific manner. The proposed methodology represents an innovative and reliable approach to the analysis of the ankle joint kinematics in pathological juvenile populations. [ABSTRACT FROM AUTHOR]

Objective: Musculoskeletal modeling has been used to predict the effect of functional electrical stimulation (FES) on the mechanics of the musculoskeletal system. However, validation of the resulting muscle activations due to FES is challenging as conventional electromyography (EMG) recording of signals from the stimulated muscle is affected by stimulation artefacts. A validation approach using a combination of musculoskeletal modeling and EMG was proposed, whereby the effect on nonstimulated muscles is assessed using both techniques. The aim is to quantify the effect of FES on biceps femoris long head (BFLH) and validate this directly against EMG of gluteus maximus (GMAX). The hypotheses are that GMAX activation correlates with BFLH activation; and the muscle activation during FES gait can be predicted using musculoskeletal modeling. Methods: Kinematics, kinetics, and EMG of healthy subjects were measured under four walking conditions (normal walking followed by FES walking with three levels of BFLH stimulation). Measured kinematics and kinetics served as inputs to the musculoskeletal model. Results: Strong positive correlations were found between GMAX activation and BFLH activation in early stance peak (R = 0.78, p = 0.002) and impulse (R = 0.63, p = 0.021). The modeled peak and impulse of GMAX activation increased with EMG peak (p < 0.001) and impulse (p = 0.021). Conclusion: Musculoskeletal modeling can be used reliably to quantify the effect of FES in a healthy gait. Significance: The validation approach using EMG and musculoskeletal modeling developed and tested can potentially be applied to the use of FES for other muscles and activities. [ABSTRACT FROM AUTHOR]

To account for proximal femoral deformities in children with cerebral palsy (CP), subject-specific musculoskeletal models are needed. Non-rigid deformation (NRD) deforms generic onto personalized bone geometry and thereby transforms the muscle points. The goal of this study was to determine to what extent the models and simulation outcomes in CP patients differ when including subject-specific detail using NRD or Magnetic Resonance Imaging (MRI)-based models. The NRD models slightly overestimated hip contact forces compared to MRI models and differences in muscle point positions and moment arm lengths (MALs) remained, although differences were smaller than for the generic model. [ABSTRACT FROM AUTHOR]

Musculoskeletal models permit the determination of internal forces acting during dynamic movement, which is clinically useful, but traditional methods may suffer from slowness and a need for extensive input data. Recently, there has been interest in the use of supervised learning to build approximate models for computationally demanding processes, with benefits in speed and flexibility. Here, we use a deep neural network to learn the mapping from movement space to muscle space. Trained on a set of kinematic, kinetic and electromyographic measurements from 156 subjects during gait, the network's predictions of internal force magnitudes show good concordance with those derived by musculoskeletal modelling. In a separate set of experiments, training on data from the most widely known benchmarks of modelling performance, the international Grand Challenge competitions, generates predictions that better those of the winning submissions in four of the six competitions. Computational speedup facilitates incorporation into a lab-based system permitting real-time estimation of forces, and interrogation of the trained neural networks provides novel insights into population-level relationships between kinematic and kinetic factors. [ABSTRACT FROM AUTHOR]

A musculoskeletal model was developed to analyze the tensions of the knee joint ligaments during walking and to understand how they change with changes in the muscle forces. The model included the femur, tibia, patella and all components of cruciate and collateral ligaments, quadriceps, hamstrings and gastrocnemius muscles. Inputs to the model were the muscle forces, estimated by a static optimization approach, the external loads (ground reaction forces and moments) and the knee flexion/extension movement corresponding to natural walking. The remaining rotational and translational movements were obtained as a result of the dynamic equilibrium of forces. The validation of the model was done by comparing our results with literature data. Several simulations were carried out by sequentially removing the forces of the different muscle groups. Deactivation of the quadriceps produced a decrease of tension in the anterior cruciate ligament (ACL) and an increase in the posterior cruciate ligament (PCL). By removing the hamstrings, the tension of ACL increased at the late swing phase, while the PCL force dropped to zero. Specific effects were observed also at the medial and lateral collateral ligaments. The removal of gastrocnemius muscles produced an increase of tension only on PCL and lateral collateral ligaments. These results demonstrate how musculoskeletal models can contribute to knowledge about complex biomechanical systems as the knee joint.

Computational studies of total knee arthroplasty (TKA) often focus on either joint mechanics (kinematics and forces) or implant fixation mechanics. However, such disconnect between joint and fixation mechanics hinders our understanding of overall TKA biomechanical function by preventing identification of key relationships between these two levels of TKA mechanics. We developed a computational workflow to holistically assess TKA biomechanics by integrating musculoskeletal and finite element (FE) models. For our initial study using the workflow, we investigated how tibiofemoral contact mechanics affected the risk of failure due to debonding at the implant-cement interface using the four available subjects from the Grand Challenge Competitions to Predict In Vivo Knee Loads. We used a musculoskeletal model with a 12 degrees-of-freedom knee joint to simulate the stance phase of gait for each subject. The computed tibiofemoral joint forces at each node in contact were direct inputs to FE simulations of the same subjects. We found that the peak risk of failure did not coincide with the peak joint forces or the extreme tibiofemoral contact positions. Moreover, despite the consistency of joint forces across subjects, we observed important variability in the profile of the risk of failure during gait. Thus, by a combined evaluation of the joint and implant fixation mechanics of TKA, we could identify subject-specific effects of joint kinematics and forces on implant fixation that would otherwise have gone unnoticed. We intend to apply our workflow to evaluate the impact of implant alignment and design on TKA biomechanics. [ABSTRACT FROM AUTHOR]

Due to lack of reference validation data, the common strategy in characterizing adolescent idiopathic scoliosis (AIS) by musculoskeletal modelling approach consists in adapting structure and parameters of validated body models of adult individuals with physiological alignments. Until now, only static postures have been replicated and investigated in AIS subjects. When aiming to simulate trunk motion, two critical factors need consideration: how distributing movement along the vertebral motion levels (lumbar spine rhythm), and if neglecting or accounting for the contribution of the stiffness of the motion segments (disc stiffness). The present study investigates the effect of three different lumbar spine rhythms and absence/presence of disc stiffness on trunk muscle imbalance in the lumbar region and on intervertebral lateral shear at different levels of the thoracolumbar/lumbar scoliotic curve, during simulated trunk motions in the three anatomical planes (flexion/extension, lateral bending, and axial rotation). A spine model with articulated ribcage previously developed in AnyBody software and adapted to replicate the spinal alignment in AIS subjects is employed. An existing dataset of 100 subjects with mild and moderate scoliosis is exploited. The results pointed out the significant impact of lumbar spine rhythm configuration and disc stiffness on changes in the evaluated outputs, as well as a relationship with scoliosis severity. Unfortunately, no optimal settings can be identified due to lack of reference validation data. According to that, extreme caution is recommended when aiming to adapt models of adult individuals with physiological alignments to adolescent subjects with scoliotic deformity. [ABSTRACT FROM AUTHOR]

Lifestyle heavily influences intervertebral disc (IVD) loads, but measuring in vivo loads requires invasive methods, and the ability to apply these loads in vitro is limited. In vivo load data from instrumented vertebral body replacements is limited to patients that have had spinal fusion surgery, potentially resulting in different kinematics and loading patterns compared to a healthy population. Therefore, this study aimed to develop a pipeline for the non-invasive estimation of in vivo IVD loading, and the application of these loads in vitro. A full-body Opensim model was developed by adapting and combining two existing models. Kinetic data from healthy participants performing activities of daily living were used as inputs for simulations using static optimisation. After evaluating simulation results using in vivo data, the estimated six-axis physiological loads were applied to bovine tail specimens. The pipeline was then used to compare the kinematics resulting from the physiological load profiles (flexion, lateral bending, axial rotation) with a simplified pure moment protocol commonly used for in vitro studies. Comparing kinematics revealed that the in vitro physiological load protocol followed the same trends as the in silico and in vivo data. Furthermore, the physiological loads resulted in substantially different kinematics when compared to pure moment testing, particularly in flexion. Therefore, the use of the presented pipeline to estimate the complex loads of daily activities in different populations, and the application of those loads in vitro provides a novel capability to deepen our knowledge of spine biomechanics, IVD mechanobiology, and improve pre-clinical test methods. [ABSTRACT FROM AUTHOR]

• Three MSK models present similar errors during gait on vertical forces estimations. • Errors in vertical forces were lower for modified model during sit-to-stand tasks. • For tasks with higher muscle demand the modified model presented lower errors. • The shear forces for all tasks showed significant errors using the three models. The choice of musculoskeletal (MSK) model is crucial for performing MSK estimations to evaluate muscle demands and joint forces. This study compared two previously published generic MSK models and a modified model to estimate tibiofemoral reaction forces (TFRF) during gait, sit-to-stand, and stand-to-sit. The estimated tibiofemoral reaction forces were compared with an in vivo dataset from six patients using an instrumented knee prosthesis. A correlation and root mean square error (RMSE) in the time-series analysis and relative peak error (RPE) were evaluated. The results showed that the three MSK models were similar in estimating the vertical forces, with a large correlation, and RPE was found around 20 % during gait. The RMSE and the RPE indicated that the modified model had lower total and lateral compartment forces errors for sit-to-stand and stand-to-sit, showing the best performance. The shear forces for all tasks and models showed significant errors. Future MSK studies should consider these findings when researching functional tasks. The modified model was found to be more effective in estimating the vertical tibiofemoral joint reaction forces in tasks that impose greater demands on muscle forces and require high knee and hip flexion. [ABSTRACT FROM AUTHOR]

Over the past decades, the use of computational physics-based models representative of the musculoskeletal (MSK) system has become increasingly popular in many fields of clinically driven research, locomotor rehabilitation in particular. These models have been applied to various functional impairments given their ability to estimate parameters which cannot be readily measured in vivo but are of interest to clinicians. The use of MSK modelling and simulations allows analysis of relevant MSK biomarkers such as muscle and joint contact loading at a number of different stages in the clinical treatment pathway in order to benefit patient functional outcome. Applications of these methods include optimisation of rehabilitation programs, patient stratification, disease characterisation, surgical pre-planning, and assistive device and exoskeleton design and optimisation. This review provides an overview of current approaches, the components of standard MSK models, applications, limitations, and assumptions of these modelling and simulation methods, and finally proposes a future direction.

This paper is the last of a three-part series that investigates the architecture of cancellous bone in the main hindlimb bones of theropod dinosaurs, and uses cancellous bone architectural patterns to infer locomotor biomechanics in extinct non-avian species. Cancellous bone is highly sensitive to its prevailing mechanical environment, and may therefore help further understanding of locomotor biomechanics in extinct tetrapod vertebrates such as dinosaurs. Here in Part III, the biomechanical modelling approach derived previously was applied to two species of extinct, non-avian theropods, Daspletosaurus torosus and Troodon formosus. Observed cancellous bone architectural patterns were linked with quasi-static, three-dimensional musculoskeletal and finite element models of the hindlimb of both species, and used to derive characteristic postures that best aligned continuum-level principal stresses with cancellous bone fabric. The posture identified for Daspletosaurus was largely upright, with a subvertical femoral orientation, whilst that identified for Troodon was more crouched, but not to the degree observed in extant birds. In addition to providing new insight on posture and limb articulation, this study also tested previous hypotheses of limb bone loading mechanics and muscular control strategies in non-avian theropods, and how these aspects evolved on the line to birds. The results support the hypothesis that an upright femoral posture is correlated with bending-dominant bone loading and abduction-based muscular support of the hip, whereas a crouched femoral posture is correlated with torsion-dominant bone loading and long-axis rotation-based muscular support. Moreover, the results of this study also support the inference that hindlimb posture, bone loading mechanics and muscular support strategies evolved in a gradual fashion along the line to extant birds.

This paper is the second of a three-part series that investigates the architecture of cancellous bone in the main hindlimb bones of theropod dinosaurs, and uses cancellous bone architectural patterns to infer locomotor biomechanics in extinct non-avian species. Cancellous bone is widely known to be highly sensitive to its mechanical environment, and therefore has the potential to provide insight into locomotor biomechanics in extinct tetrapod vertebrates such as dinosaurs. Here in Part II, a new biomechanical modelling approach is outlined, one which mechanistically links cancellous bone architectural patterns with three-dimensional musculoskeletal and finite element modelling of the hindlimb. In particular, the architecture of cancellous bone is used to derive a single ‘characteristic posture’ for a given species—one in which bone continuum-level principal stresses best align with cancellous bone fabric—and thereby clarify hindlimb locomotor biomechanics. The quasi-static approach was validated for an extant theropod, the chicken, and is shown to provide a good estimate of limb posture at around mid-stance. It also provides reasonable predictions of bone loading mechanics, especially for the proximal hindlimb, and also provides a broadly accurate assessment of muscle recruitment insofar as limb stabilization is concerned. In addition to being useful for better understanding locomotor biomechanics in extant species, the approach hence provides a new avenue by which to analyse, test and refine palaeobiomechanical hypotheses, not just for extinct theropods, but potentially many other extinct tetrapod groups as well.

Exoskeletons and other wearable robotic devices have a wide range of potential applications, including assisting patients with walking pathologies, acting as tools for rehabilitation, and enhancing the capabilities of healthy humans. However, applying these devices effectively in a real-world setting can be challenging, as the optimal design features and control commands for an exoskeleton are highly dependent on the current user, task and environment. Consequently, robust metrics and methods for quantifying exoskeleton performance are required. This work presents an analysis of walking data collected for healthy subjects walking with an active pelvis exoskeleton over three assistance scenarios and five walking contexts. Spatial and temporal, kinematic, kinetic and other novel dynamic gait metrics were compared to identify which metrics exhibit desirable invariance properties, and so are good candidates for use as a stability metric over varying walking conditions. Additionally, using a model-based approach, the average metabolic power consumption was calculated for a subset of muscles crossing the hip, knee and ankle joints, and used to analyse how the energy-reducing properties of an exoskeleton are affected by changes in walking context. The results demonstrated that medio-lateral centre of pressure displacement and medio-lateral margin of stability exhibit strong invariance to changes in walking conditions. This suggests that these dynamic gait metrics are optimised in human gait and are potentially suitable metrics for optimising in an exoskeleton control paradigm. The effectiveness of the exoskeleton at reducing human energy expenditure was observed to increase when walking on an incline, where muscles aiding in hip flexion were assisted, but decrease when walking at a slow speed. These results underline the need for adaptive control algorithms for exoskeletons if they are to be used in varied environments.

Back support exosuits aim to reduce tissue demands and thereby risk of injury and pain. However, biomechanical analyses of soft active exosuit designs have been limited. The objective of this study was to evaluate the effect of a soft active back support exosuit on trunk motion and thoracolumbar spine loading in participants performing stoop and squat lifts of 6 and 10 kg crates, using participant-specific musculoskeletal models. The exosuit did not change overall trunk motion but affected lumbo-pelvic motion slightly, and reduced peak compressive and shear vertebral loads at some levels, although shear increased slightly at others. This study indicates that soft active exosuits have limited kinematic effects during lifting, and can reduce spinal loading depending on the vertebral level. These results support the hypothesis that a soft exosuit can assist without limiting trunk movement or negatively impacting skeletal loading and have implications for future design and ergonomic intervention efforts.