In-silico study of the biomechanical effects of proximal-fibular osteotomy on knee joint contact pressure in varus-valgus misalignment.

The aim of this work is to investigate in-silico the biomechanical effects of a proximal fibular osteotomy (PFO) on a knee joint with different varus/valgus deformities on the progression of knee osteoarthritis (KOA). A finite element analysis (FEA) of a human lower extremity consisting of the femoral, tibial and fibular bones and the cartilage connecting them was designed. The FEA was performed in a static standing primitive position to determine the contact pressure (CP) distribution and the location of the center of pressure (CoP). The analysis examined the relationship between these factors and the degree of deformation of the hip-knee angle in the baseline condition. The results suggested that PFO could be a simple and effective surgical treatment for patients with associated genu varum. This work also reported that a possible CP homogenization and a CoP correction can be achieved for medial varus deformities after PFO. However, it reduced its effectiveness for tibial origin valgus misalignment and worsened in cases of femoral valgus misalignment.

How effective is proximal fibular osteotomy in redistributing joint pressures? Insights from an HTO comparative in-silico study.

BACKGROUND: Knee osteoarthritis (KOA) represents a widespread degenerative condition among adults that significantly affects quality of life. This study aims to elucidate the biomechanical implications of proximal fibular osteotomy (PFO), a proposed cost-effective and straightforward intervention for KOA, comparing its effects against traditional high tibial osteotomy (HTO) through in-silico analysis. METHODS: Using medical imaging and finite element analysis (FEA), this research quantitatively evaluates the biomechanical outcomes of a simulated PFO procedure in patients with severe medial compartment genu-varum, who have undergone surgical correction with HTO. The study focused on evaluating changes in knee joint contact pressures, stress distribution, and anatomical positioning of the center of pressure (CoP). Three models are generated for each of the five patients investigated in this study, a preoperative original condition model, an in-silico PFO based on the same original condition data, and a reversed-engineered HTO in-silico model. RESULTS: The novel contribution of this investigation is the quantitative analysis of the impact of PFO on the biomechanics of the knee joint. The results provide mechanical evidence that PFO can effectively redistribute and homogenize joint stresses, while also repositioning the CoP towards the center of the knee, similar to what is observed post HTO. The findings propose PFO as a potentially viable and simpler alternative to conventional surgical methods for managing severe KOA, specifically in patients with medial compartment genu-varum. CONCLUSION: This research also marks the first application of FEA that may support one of the underlying biomechanical theories of PFO, providing a foundation for future clinical and in-silico studies.

Optimal fibre length and maximum isometric force are the most influential parameters when modelling muscular adaptations to unloading using Hill-type muscle models.

Introduction: Spaceflight is associated with severe muscular adaptations with substantial inter-individual variability. A Hill-type muscle model is a common method to replicate muscle physiology in musculoskeletal simulations, but little is known about how the underlying parameters should be adjusted to model adaptations to unloading. The aim of this study was to determine how Hill-type muscle model parameters should be adjusted to model disuse muscular adaptations. Methods: Isokinetic dynamometer data were taken from a bed rest campaign and used to perform tracking simulations at two knee extension angular velocities (30°·s-1 and 180°·s-1). The activation and contraction dynamics were solved using an optimal control approach and direct collocation method. A Monte Carlo sampling technique was used to perturb muscle model parameters within physiological boundaries to create a range of theoretical and feasible parameters to model muscle adaptations. Results: Optimal fibre length could not be shortened by more than 67% and 61% for the knee flexors and non-knee muscles, respectively. Discussion: The Hill-type muscle model successfully replicated muscular adaptations due to unloading, and recreated salient features of muscle behaviour associated with spaceflight, such as altered force-length behaviour. Future researchers should carefully adjust the optimal fibre lengths of their muscle-models when trying to model adaptations to unloading, particularly muscles that primarily operate on the ascending and descending limbs of the force-length relationship.

A novel computational framework for the estimation of internal musculoskeletal loading and muscle adaptation in hypogravity.

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.

Criterion validity of neural networks to assess lower limb motion during cycling.

The use of marker-less methods to automatically obtain kinematics of movement is expanding but validity to high-velocity tasks such as cycling with the presence of the bicycle on the field of view is needed when standard video footage is obtained. The purpose of this study was to assess if pre-trained neural networks are valid for calculations of lower limb joint kinematics during cycling. Motion of twenty-six cyclists pedalling on a cycle trainer was captured by a video camera capturing frames from the sagittal plane whilst reflective markers were attached to their lower limb. The marker-tracking method was compared to two established deep learning-based approaches (Microsoft Research Asia-MSRA and OpenPose) to estimate hip, knee and ankle joint angles. Poor to moderate agreement was found for both methods, with OpenPose differing from the criterion by 4-8° for the hip and knee joints. Larger errors were observed for the ankle joint (15-22°) but no significant differences between methods throughout the crank cycle when assessed using Statistical Parametric Mapping were observed for any of the joints. OpenPose presented stronger agreement with marker-tracking (criterion) than the MSRA for the hip and knee joints but resulted in poor agreement for the ankle joint.

Validity of Neural Networks to Determine Body Position on the Bicycle.

Purpose: With the increased access to neural networks trained to estimate body segments from images and videos, this study assessed the validity of some of these networks in enabling the assessment of body position on the bicycle. Methods: Fourteen cyclists pedaled stationarily in one session on their own bicycles while video was recorded from their sagittal plane. Reflective markers attached to key bony landmarks were used to manually digitize joint angles at two positions of the crank (3 o'clock and 6 o'clock) extracted from the videos (Reference method). These angles were compared to measurements taken from videos generated by two deep learning-based approaches designed to automatically estimate human joints (Microsoft Research Asia-MSRA and OpenPose). Results: Mean bias for OpenPose ranged between 0.03° and 1.81°, while the MSRA method presented errors between 2.29° and 12.15°. Correlation coefficients were stronger for OpenPose than for the MSRA method in relation to the Reference method for the torso (r = 0.94 vs. 0.92), hip (r = 0.69 vs. 0.60), knee (r = 0.80 vs. 0.71), and ankle (r = 0.23 vs. 0.20). Conclusion: OpenPose presented better accuracy than the MSRA method in determining body position on the bicycle, but both methods seem comparable in assessing implications from changes in bicycle configuration.

A feasibility study to assess the effectiveness of Muvity: A telerehabilitation system for chronic post-stroke subjects.

OBJECTIVES: To assess the feasibility of a telerehabilitation system for chronic post-stroke subjects compared to a conventional treatment. METHODS: A feasibility cross-over analysis was conducted in ten chronic post-stroke subjects. Two randomized groups followed two eight-weeks treatments, one with the telerehabilitation system Muvity and the other following conventional therapy (in random order). Before and after each treatment, physical evaluations were performed assessing functional independence, the perceived level of pain, balance control and self-reported health status. After the study, the participants answered a short questionnaire to measure the usability of the system. RESULTS: Four out of six subjects demonstrated better performance in ADLs (equal or higher FIM scores) and five out of six reported lower pain (VAS score) after the treatment with Muvity when compared to the treatment without. There were no clear trends in terms of balance control (Berg scale) or self-reported health status (PCS score within SF-36). CONCLUSIONS: The results suggest that the proposed telerehabilitation system aids users to overall maintain or improve their ability to perform ADLs without increasing pain, when compared to conventional therapy. Most subjects found the use of Muvity more motivating than the conventional rehabilitation treatment. This provides initial evidence that Muvity might be an appropriate complement for the telerehabilitation of patients with physical disabilities. However, the differences observed between both treatments were not statistically significant. A clinical study with a larger sample size will be necessary to obtain more robust results.

Modifications to the net knee moments lead to the greatest improvements in accelerative sprinting performance: a predictive simulation study.

The current body of sprinting biomechanics literature together with the front-side mechanics coaching framework provide various technique recommendations for improving performance. However, few studies have attempted to systematically explore technique modifications from a performance enhancement perspective. The aims of this investigation were therefore to explore how hypothetical technique modifications affect accelerative sprinting performance and assess whether the hypothetical modifications support the front-side mechanics coaching framework. A three-dimensional musculoskeletal model scaled to an international male sprinter was used in combination with direct collocation optimal control to perform (data-tracking and predictive) simulations of the preliminary steps of accelerative sprinting. The predictive simulations differed in the net joint moments that were left 'free' to change. It was found that the 'knee-free' and 'knee-hip-free' simulations resulted in the greatest performance improvements (13.8% and 21.9%, respectively), due to a greater knee flexor moment around touchdown (e.g., 141.2 vs. 70.5 Nm) and a delayed and greater knee extensor moment during stance (e.g., 188.5 vs. 137.5 Nm). Lastly, the predictive simulations which led to the greatest improvements were also found to not exhibit clear and noticeable front-side mechanics technique, thus the underpinning principles of the coaching framework may not be the only key aspect governing accelerative sprinting.

A Mediterranean-Style Diet Plan Is Associated with Greater Effectiveness and Sustainability in Weight Loss in Patients with Obesity after Endoscopic Bariatric Therapy.

This study aimed to investigate the impact of a Mediterranean-style diet on weight loss effectiveness and sustainability in patients with obesity who underwent endoscopic bariatric therapies (EBT), relative to a protein diet plan. Thus, 132 patients with obesity (BMI 30-40 kg/m2) who underwent EBT, were asked to follow a Mediterranean-style diet plan (n = 52) or a protein diet plan (n = 26) for six months. General linear models were used to compare outcome variables between dietary intervention groups. Results showed that participants who followed a Mediterranean-style diet plan lost 14.2% more weight (95% CI: 3.0; 25.3), compared with those who followed a protein diet plan. Additionally, following a Mediterranean-style diet plan was associated with the sustainability of weight loss. Note that three months after the end of the dietary intervention, the patients who followed a Mediterranean-style diet plan were still losing weight (-1.2 ± 3.0 kg), while those with a protein diet plan gained, on average, 2.4 ± 3.3 kg (p < 0.001). Therefore, we conclude that combining EBT with a Mediterranean-style diet plan could represent an effective dietary intervention to improve the effectiveness and sustainability of weight loss after an EBT.

Lateral extraarticular tenodesis improves stability in non-anatomic ACL reconstructed knees: in vivo kinematic analysis.

PURPOSE: To carry out an in vivo kinematic analysis to determine whether adding a lateral extraarticular tenodesis (LET) for those patients with subjective instability and objective residual laxity after a transtibial (TT) anterior cruciate ligament reconstruction (ACLR) reduces anteroposterior and rotational laxity and to evaluate the 2-year follow-up clinical outcomes to analyze whether biomechanical changes determine clinical improvement or not. METHODS: A total of 19 patients with residual knee instability after TT ACLR who underwent a modified Lemaire LET were prospectively evaluated for at least 2-year follow-up. Preoperative, intraoperative, and 6 and 24-month postoperative kinematic analyses were carried out using the KiRA accelerometer and KT1000 arthrometer to look for residual anterolateral rotational instability and residual anteroposterior instability. Functional outcomes were measured with the single-leg vertical jump test and the single-leg hop test. Clinical outcomes were evaluated using the IKDC 2000, Lysholm, and Tegner scores. RESULTS: A significant reduction in anterolateral rotational instability was detected with the patient under anesthesia (from 3 ± 1.2 to 1.1 ± 1.1 m/s2; p < 0.05) as well as with the patient awake (from 2.1 ± 0.8 to 0.7 ± 1.4 m/s2; p < 0.05). A significant reduction in anteroposterior instability was only present under anesthesia (from 3.4 ± 1.9 to 2.1 ± 1.1 mm; p < 0.05), while no difference was present without anesthesia (from 2.3 ± 1.1 to 1.6 ± 1 mm; n.s.). Postoperative analysis of knee laxity did not show any significant variation from the first to the last follow-up. Both the single-leg vertical jump test and single-leg hop test improved significantly at the last follow-up (both p < 0.05). The mean values of both the IKDC and Tegner scores showed an improvement (p < 0.05 and p < 0.05, respectively), whereas that was not the case with the Lysholm score (n.s.). CONCLUSIONS: The modified Lemaire LET can improve the kinematics of a non-anatomic ACL reconstructed knee with residual subjective and objective instability. These kinematic changes were able to lead to an improvement in subjective stability as well as the function of the knee in a small cohort of recreationally active patients. At 2-year follow-up, the kinematic changes as well as the level of activity of the patients and the IKDC score show their improvement sustained. LEVEL OF EVIDENCE: Level IV.

A factorization-based algorithm to predict EMG data using only kinematics information.

EMG analyses have several applications, such as identifying muscle excitation patterns during rehabilitation or training plans, or controlling EMG-driven devices. However, experimental measurements can be time consuming or difficult to obtain. This study presents a simple algorithm to predict EMG signals that can be applied in real time during running, given only the instantaneous vector of kinematics. We hypothesize that the factorization of the kinematics of the skeleton together with the EMG data of calibration subjects could be used to predict EMG data of another subject only using the kinematic information. The results showed that EMG signals of lower-limb muscles can be predicted accurately in less than a second using this method. Correlation coefficients between predicted and experimental EMG signals were higher than 0.7 in 10 out of 11 muscles for most prediction trials and subjects, and their overall median value was higher than 0.8. These values confirm that this method could be used to accurately predict EMG signals in real time when only kinematics are measured.

The Effects of Mechanical Scale on Neural Control and the Regulation of Joint Stability.

Recent work has demonstrated how the size of an animal can affect neural control strategies, showing that passive viscoelastic limb properties have a significant role in determining limb movements in small animals but are less important in large animals. We extend that work to consider effects of mechanical scaling on the maintenance of joint integrity; i.e., the prevention of aberrant contact forces within joints that might lead to joint dislocation or cartilage degradation. We first performed a literature review to evaluate how properties of ligaments responsible for joint integrity scale with animal size. Although we found that the cross-sectional area of the anterior cruciate ligament generally scaled with animal size, as expected, the effects of scale on the ligament's mechanical properties were less clear, suggesting potential adaptations in passive contributions to the maintenance of joint integrity across species. We then analyzed how the neural control of joint stability is altered by body scale. We show how neural control strategies change across mechanical scales, how this scaling is affected by passive muscle properties and the cost function used to specify muscle activations, and the consequences of scaling on internal joint contact forces. This work provides insights into how scale affects the regulation of joint integrity by both passive and active processes and provides directions for studies examining how this regulation might be accomplished by neural systems.

Three-dimensional data-tracking simulations of sprinting using a direct collocation optimal control approach.

Biomechanical simulation and modelling approaches have the possibility to make a meaningful impact within applied sports settings, such as sprinting. However, for this to be realised, such approaches must first undergo a thorough quantitative evaluation against experimental data. We developed a musculoskeletal modelling and simulation framework for sprinting, with the objective to evaluate its ability to reproduce experimental kinematics and kinetics data for different sprinting phases. This was achieved by performing a series of data-tracking calibration (individual and simultaneous) and validation simulations, that also featured the generation of dynamically consistent simulated outputs and the determination of foot-ground contact model parameters. The simulated values from the calibration simulations were found to be in close agreement with the corresponding experimental data, particularly for the kinematics (average root mean squared differences (RMSDs) less than 1.0° and 0.2 cm for the rotational and translational kinematics, respectively) and ground reaction force (highest average percentage RMSD of 8.1%). Minimal differences in tracking performance were observed when concurrently determining the foot-ground contact model parameters from each of the individual or simultaneous calibration simulations. The validation simulation yielded results that were comparable (RMSDs less than 1.0° and 0.3 cm for the rotational and translational kinematics, respectively) to those obtained from the calibration simulations. This study demonstrated the suitability of the proposed framework for performing future predictive simulations of sprinting, and gives confidence in its use to assess the cause-effect relationships of technique modification in relation to performance. Furthermore, this is the first study to provide dynamically consistent three-dimensional muscle-driven simulations of sprinting across different phases.

Personalised high tibial osteotomy has mechanical safety equivalent to generic device in a case-control in silico clinical trial.

Background: Despite favourable outcomes relatively few surgeons offer high tibial osteotomy (HTO) as a treatment option for early knee osteoarthritis, mainly due to the difficulty of achieving planned correction and reported soft tissue irritation around the plate used to stablise the osteotomy. To compare the mechanical safety of a new personalised 3D printed high tibial osteotomy (HTO) device, created to overcome these issues, with an existing generic device, a case-control in silico virtual clinical trial was conducted. Methods: Twenty-eight knee osteoarthritis patients underwent computed tomography (CT) scanning to create a virtual cohort; the cohort was duplicated to form two arms, Generic and Personalised, on which virtual HTO was performed. Finite element analysis was performed to calculate the stresses in the plates arising from simulated physiological activities at three healing stages. The odds ratio indicative of the relative risk of fatigue failure of the HTO plates between the personalised and generic arms was obtained from a multi-level logistic model. Results: Here we show, at 12 weeks post-surgery, the odds ratio indicative of the relative risk of fatigue failure was 0.14 (95%CI 0.01 to 2.73, p = 0.20). Conclusions: This novel (to the best of our knowledge) in silico trial, comparing the mechanical safety of a new personalised 3D printed high tibial osteotomy device with an existing generic device, shows that there is no increased risk of failure for the new personalised design compared to the existing generic commonly used device. Personalised high tibial osteotomy can overcome the main technical barriers for this type of surgery, our findings support the case for using this technology for treating early knee osteoarthritis.

Personalised high tibial osteotomy has mechanical safety equivalent to generic device in a case-control in silico clinical trial.

BACKGROUND: Despite favourable outcomes relatively few surgeons offer high tibial osteotomy (HTO) as a treatment option for early knee osteoarthritis, mainly due to the difficulty of achieving planned correction and reported soft tissue irritation around the plate used to stablise the osteotomy. To compare the mechanical safety of a new personalised 3D printed high tibial osteotomy (HTO) device, created to overcome these issues, with an existing generic device, a case-control in silico virtual clinical trial was conducted. METHODS: Twenty-eight knee osteoarthritis patients underwent computed tomography (CT) scanning to create a virtual cohort; the cohort was duplicated to form two arms, Generic and Personalised, on which virtual HTO was performed. Finite element analysis was performed to calculate the stresses in the plates arising from simulated physiological activities at three healing stages. The odds ratio indicative of the relative risk of fatigue failure of the HTO plates between the personalised and generic arms was obtained from a multi-level logistic model. RESULTS: Here we show, at 12 weeks post-surgery, the odds ratio indicative of the relative risk of fatigue failure was 0.14 (95%CI 0.01 to 2.73, p = 0.20). CONCLUSIONS: This novel (to the best of our knowledge) in silico trial, comparing the mechanical safety of a new personalised 3D printed high tibial osteotomy device with an existing generic device, shows that there is no increased risk of failure for the new personalised design compared to the existing generic commonly used device. Personalised high tibial osteotomy can overcome the main technical barriers for this type of surgery, our findings support the case for using this technology for treating early knee osteoarthritis.

Surgical treatment to realign the knee, called a high tibial osteotomy, is effective at relieving symptoms of knee osteoarthritis but the operation is difficult. A new personalised treatment with simpler surgery has been designed. The aim of this study was to investigate the safety of the new personalised treatment compared to the standard treatment. For the first time, a detailed computer simulation clinical trial was performed, using imaging data from 28 real patients. The computer simulation compared the risk of the implant failure between the personalised and standard treatments. The personalised treatment did not have a higher risk of implant failure than standard treatment. This supports further clinical studies looking at the benefits of personalised over standard realignment surgery. The personalised treatment has the potential to allow much more widespread use of realignment surgery to treat early knee osteoarthritis.

Influence of musculoskeletal model parameter values on prediction of accurate knee contact forces during walking.

Treatment design for musculoskeletal disorders using in silico patient-specific dynamic simulations is becoming a clinical possibility. However, these simulations are sensitive to model parameter values that are difficult to measure experimentally, and the influence of uncertainties in these parameter values on the accuracy of estimated knee contact forces remains unknown. This study evaluates which musculoskeletal model parameters have the greatest influence on estimating accurate knee contact forces during walking. We performed the evaluation using a two-level optimization algorithm where musculoskeletal model parameter values were adjusted in the outer level and muscle activations were estimated in the inner level. We tested the algorithm with different sets of design variables (combinations of optimal muscle fiber lengths, tendon slack lengths, and muscle moment arm offsets) resulting in nine different optimization problems. The most accurate lateral knee contact force predictions were obtained when tendon slack lengths and moment arm offsets were adjusted simultaneously, and the most accurate medial knee contact force estimations were obtained when all three types of parameters were adjusted together. Inclusion of moment arm offsets as design variables was more important than including either tendon slack lengths or optimal muscle fiber lengths alone to obtain accurate medial and lateral knee contact force predictions. These results provide guidance on which musculoskeletal model parameter values should be calibrated when seeking to predict in vivo knee contact forces accurately.

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement.

Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. The secondary aim was to evaluate computational choices including different AD tools, different linear solvers, and the use of first- or second-order derivatives. First, we enabled the use of AD in OpenSim through a custom source code transformation tool and through the operator overloading tool ADOL-C. Second, we developed an interface between OpenSim and CasADi to solve trajectory optimization problems. Third, we evaluated computational choices through simulations of perturbed balance, two-dimensional predictive simulations of walking, and three-dimensional tracking simulations of walking. We performed all simulations using direct collocation and implicit differential equations. Using AD through our custom tool was between 1.8 ± 0.1 and 17.8 ± 4.9 times faster than using FD, and between 3.6 ± 0.3 and 12.3 ± 1.3 times faster than using AD through ADOL-C. The linear solver efficiency was problem-dependent and no solver was consistently more efficient. Using second-order derivatives was more efficient for balance simulations but less efficient for walking simulations. The walking simulations were physiologically realistic. These results highlight how the use of AD drastically decreases computational time of trajectory optimization problems as compared to more common FD. Overall, combining AD with direct collocation and implicit differential equations decreases the computational burden of trajectory optimization of human movement, which will facilitate their use for biomechanical applications requiring the use of detailed models of the musculoskeletal system.

Rapid predictive simulations with complex musculoskeletal models suggest that diverse healthy and pathological human gaits can emerge from similar control strategies.

Physics-based predictive simulations of human movement have the potential to support personalized medicine, but large computational costs and difficulties to model control strategies have limited their use. We have developed a computationally efficient optimal control framework to predict human gaits based on optimization of a performance criterion without relying on experimental data. The framework generates three-dimensional muscle-driven simulations in 36 min on average-more than 20 times faster than existing simulations-by using direct collocation, implicit differential equations and algorithmic differentiation. Using this framework, we identified a multi-objective performance criterion combining energy and effort considerations that produces physiologically realistic walking gaits. The same criterion also predicted the walk-to-run transition and clinical gait deficiencies caused by muscle weakness and prosthesis use, suggesting that diverse healthy and pathological gaits can emerge from the same control strategy. The ability to predict the mechanics and energetics of a broad range of gaits with complex three-dimensional musculoskeletal models will allow testing novel hypotheses about gait control and hasten the development of optimal treatments for neuro-musculoskeletal disorders.

Subject-Exoskeleton Contact Model Calibration Leads to Accurate Interaction Force Predictions.

Knowledge of human-exoskeleton interaction forces is crucial to assess user comfort and effectiveness of the interaction. The subject-exoskeleton collaborative movement and its interaction forces can be predicted in silico using computational modeling techniques. We developed an optimal control framework that consisted of three phases. First, the foot-ground (Phase A) and the subject-exoskeleton (Phase B) contact models were calibrated using three experimental sit-to-stand trials. Then, the collaborative movement and the subject-exoskeleton interaction forces, of six different sit-to-stand trials were predicted (Phase C). The results show that the contact models were able to reproduce experimental kinematics of calibration trials (mean root mean square differences - RMSD - coordinates ≤ 1.1° and velocities ≤ 6.8°/s), ground reaction forces (mean RMSD≤ 22.9 N), as well as the interaction forces at the pelvis, thigh, and shank (mean RMSD ≤ 5.4 N). Phase C could predict the collaborative movements of prediction trials (mean RMSD coordinates ≤ 3.5° and velocities ≤ 15.0°/s), and their subject-exoskeleton interaction forces (mean RMSD ≤ 13.1° N). In conclusion, this optimal control framework could be used while designing exoskeletons to have in silico knowledge of new optimal movements and their interaction forces.

Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking.

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and -0.10 lateral). Approach B had statistically higher lateral muscle forces and lateral optimal muscle fiber lengths but lower medial, central, and lateral normalized muscle fiber lengths compared to Approach A. These findings suggest that poorly calibrated model parameter values may be a major factor limiting the ability of neuromusculoskeletal models to predict knee contact and leg muscle forces accurately for walking.