Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces

Relationship between knee joint contact forces and external knee joint moments in patients with medial knee osteoarthritis: effects of gait modifications

OBJECTIVE

To evaluate 1) the relationship between the knee contact force (KCF) and knee adduction and flexion moments (KAM and KFM) during normal gait in people with medial knee osteoarthritis (KOA), 2) the effects on the KCF of walking with a modified gait pattern and 3) the relationship between changes in the KCF and changes in the knee moments.

METHOD

We modeled the gait biomechanics of thirty-five patients with medial KOA using the AnyBody Modeling System during normal gait and two modified gait patterns. We calculated the internal KCF and evaluated the external joint moments (KAM and KFM) against it using linear regression analyses.

RESULTS

First peak medial KCF was associated with first peak KAM (R² = 0.60) and with KAM and KFM (R² = 0.73). Walking with both modified gait patterns reduced KAM (P = 0.002) and the medial to total KCF ratio (P < 0.001) at the first peak. Changes in KAM during modified gait were moderately associated with changes in the medial KCF at the first peak (R² = 0.54 and 0.53).

CONCLUSIONS

At the first peak, KAM is a reasonable substitute for the medial contact force, but not at the second peak. First peak KFM is also a significant contributor to the medial KCF. At the first peak, walking with a modified gait reduced the ratio of the medial to total KCF but not the medial KCF itself. To determine the effects of gait modifications on cartilage loading and disease progression, longitudinal studies and individualized modeling, accounting for motion control, would be required.

Application of quality by design for 3D printed bone prostheses and scaffolds

3D printing is an emergent manufacturing technology recently being applied in the medical field for the development of custom bone prostheses and scaffolds. However, successful industry transformation to this new design and manufacturing approach requires technology integration, concurrent multi-disciplinary collaboration, and a robust quality management framework. This latter change enabler is the focus of this study. While a number of comprehensive quality frameworks have been developed in recent decades to ensure that the manufacturing of medical devices produces reliable products, they are centred on the traditional context of standardised manufacturing techniques. The advent of 3D printing technologies and the prospects for mass customisation provides significant market opportunities, but also presents a serious challenge to regulatory bodies tasked with managing and assuring product quality and safety. Before 3D printing bone prostheses and scaffolds can gain traction, industry stakeholders, such as regulators, clients, medical practitioners, insurers, lawyers, and manufacturers, would all require a high degree of confidence that customised manufacturing can achieve the same quality outcomes as standardised manufacturing. A Quality by Design (QbD) approach to custom 3D printed prostheses can help to ensure that products are designed and manufactured correctly from the beginning without errors. This paper reports on the adaptation of the QbD approach for the development process of 3D printed custom bone prosthesis and scaffolds. This was achieved through the identification of the Critical Quality Attributes of such products, and an extensive review of different design and fabrication methods for 3D printed bone prostheses. Research outcomes include the development of a comprehensive design and fabrication process flow diagram, and categorised risks associated with the design and fabrication processes of such products. An extensive systematic literature review and post-hoc evaluation survey with experts was completed to evaluate the likely effectiveness of the herein suggested QbD framework.

Design-validation of a hand exoskeleton using musculoskeletal modeling

Exoskeletons are progressively reaching homes and workplaces, allowing interaction with virtual environments, remote control of robots, or assisting human operators in carrying heavy loads. Their design is however still a challenge as these robots, being mechanically linked to the operators who wear them, have to meet ergonomic constraints besides usual robotic requirements in terms of workspace, speed, or efforts. They have in particular to fit the anthropometry and mobility of their users. This traditionally results in numerous prototypes which are progressively fitted to each individual person. In this paper, we propose instead to validate the design of a hand exoskeleton in a fully digital environment, without the need for a physical prototype. The purpose of this study is thus to examine whether finger kinematics are altered when using a given hand exoskeleton. Therefore, user specific musculoskeletal models were created and driven by a motion capture system to evaluate the fingers' joint kinematics when performing two industrial related tasks. The kinematic chain of the exoskeleton was added to the musculoskeletal models and its compliance with the hand movements was evaluated. Our results show that the proposed exoskeleton design does not influence fingers' joints angles, the coefficient of determination between the model with and without exoskeleton being consistently high (R²¯=0.93) and the nRMSE consistently low (nRMSE¯ = 5.42°). These results are promising and this approach combining musculoskeletal and robotic modeling driven by motion capture data could be a key factor in the ergonomics validation of the design of orthotic devices and exoskeletons prior to manufacturing.

Effect of foot progression angle adjustment on the knee adduction moment and knee joint contact force in runners with and without knee osteoarthritis

BACKGROUND

Knee adduction moment (KAM) is often used as a surrogate marker of knee contact force (KCF) during walking. Previous studies have reported potential benefits to reduce KAM in patients with knee osteoarthritis (OA) by foot progression angle adjustment. However, KAM is an external moment and it does not consider any muscle contribution to the joint loading, which should pose a greater influence in running than walking.

RESEARCH QUESTION

This study used a computational model to compare KAM and KCF between runners with and without knee OA during running. In addition, we evaluated the KAM and KCF when runners adjusted to an out-toe running style.

METHODS

Kinematic, kinetic, and lower limb EMG data were collected from 9 runners with knee OA and 10 healthy counterparts. They were asked to run at their usual speed with standard shoes on an instrumented treadmill.

RESULTS

We found no significant difference in the KAM during running between OA and the healthy group (p > 0.376). However, runners with knee OA exhibited a greater total KCF than the healthy counterparts (p < 0.041). We did not observe any reduction in KAM after foot progression angle adjustment (p > 0.346). Surprisingly, an increase in the longitudinal KCF and total KCF were found with adjustment of foot progression angle (p < 0.046).

SIGNIFICANCE

Unlike the findings reported by the previous walking trials, our findings do not support the notion that foot progression angle adjustment would lead to a lower joint loading during running.

Knee medial and lateral contact forces in a musculoskeletal model with subject-specific contact point trajectories

Contact point (CP) trajectory is a crucial parameter in estimating medial/lateral tibio-femoral contact forces from the musculoskeletal (MSK) models. The objective of the present study was to develop a method to incorporate the subject-specific CP trajectories into the MSK model. Ten healthy subjects performed 45 s treadmill gait trials. The subject-specific CP trajectories were constructed on the tibia and femur as a function of extension-flexion using low-dose bi-plane X-ray images during a quasi-static squat. At each extension-flexion position, the tibia and femur CPs were superimposed in the three directions on the medial side, and in the anterior-posterior and proximal-distal directions on the lateral side to form the five kinematic constraints of the knee joint. The Lagrange multipliers associated to these constraints directly yielded the medial/lateral contact forces. The results from the personalized CP trajectory model were compared against the linear CP trajectory and sphere-on-plane CP trajectory models which were adapted from the commonly used MSK models. Changing the CP trajectory had a remarkable impact on the knee kinematics and changed the medial and lateral contact forces by 1.03 BW and 0.65 BW respectively, in certain subjects. The direction and magnitude of the medial/lateral contact force were highly variable among the subjects and the medial-lateral shift of the CPs alone could not determine the increase/decrease pattern of the contact forces. The suggested kinematic constraints are adaptable to the CP trajectories derived from a variety of joint models and those experimentally measured from the 3D imaging techniques.

Force Closure Mechanism Modeling for Musculoskeletal Multibody Simulation

OBJECTIVE

Neuro-musculoskeletal multibody simulation (NMBS) seeks to optimize decision-making for patients with neuro-musculoskeletal disorders. In clinical practice, however, the inter-subject variability and the inaccessibility for experimental testing impede the reliable model identification. These limitations motivate the novel modeling approach termed as force closure mechanism modeling (FCM²).

METHODS

FCM ² expresses the dynamics between mutually articulating joint partners with respect to instantaneous screw axes (ISA) automatically reconstructed from their relative velocity state. Thereby, FCM² reduces arbitrary open-chain multibody topologies to force closure n-link pendulums. Within a computational validation study on the human knee joint with implemented contact surfaces, we examine FCM² as an underlying inverse dynamic model for computed muscle control. We evaluate predicted tibiofemoral joint quantities, i.e., kinematics and contact forces along with muscle moment arms, during muscle-induced knee motion against the classic hinge joint model and experimental studies.

RESULTS

Our NMBS study provided the proof-of-principle of the novel modeling approach. FCM² freed us from assuming a certain joint formulation while correctly predicting the joint dynamics in agreement with the established methods. Although experimental results were closely predicted, owing to noise in the ISA estimation, muscle moment arms were overestimated (R_ISA = 0.84 < R_HINGE = 0.97, RMSE_ISA = 13.18 mm > RMSE_HINGE = 6.54 mm), identifying the robust ISA estimation as key to FCM².

CONCLUSION

FCM² automatically derives the equations of motion in closed form. Moreover, it captures subject-specific joint function and, thereby, minimizes modeling and parameterization efforts.

SIGNIFICANCE

Model derivation becomes driven by quantitative data available in clinical settings so that FCM² yields a promising framework toward subject-specific NMBS.

A Novel Ultrasound-Based Lower Extremity Motion Tracking System

Tracking joint motion of the lower extremity is important for human motion analysis. In this study, we present a novel ultrasound-based motion tracking system for measuring three-dimensional (3D) position and orientation of the femur and tibia in 3D space and quantifying tibiofemoral kinematics under dynamic conditions. As ultrasound is capable of detecting underlying bone surface noninvasively through multiple layers of soft tissues, an integration of multiple A-mode ultrasound transducers with a conventional motion tracking system provides a new approach to track the motion of bone segments during dynamic conditions. To demonstrate the technical and clinical feasibilities of this concept, an in vivo experiment was conducted. For this purpose the kinematics of healthy individuals were determined in treadmill walking conditions and stair descending tasks. The results clearly demonstrated the potential of tracking skeletal motion of the lower extremity and measuring six-degrees-of-freedom (6-DOF) tibiofemoral kinematics and related kinematic alterations caused by a variety of gait parameters. It was concluded that this prototyping system has great potential to measure human kinematics in an ambulant, non-radiative, and noninvasive manner.

Load application for the contact mechanics analysis and wear prediction of total knee replacement

Tibiofemoral contact forces in total knee replacement have been measured at the medial and lateral sites respectively using an instrumented prosthesis, and predicted from musculoskeletal multibody dynamics models with a reasonable accuracy. However, it is uncommon that the medial and lateral forces are applied separately to replace a total axial load according to the ISO standard in the majority of current finite element analyses. In this study, we quantified the different effects of applying the medial and lateral loads separately versus the traditional total axial load application on contact mechanics and wear prediction of a patient-specific knee prosthesis. The load application position played an important role under the medial-lateral load application. The loading set which produced the closest load distribution to the multibody dynamics model was used to predict the contact mechanics and wear for the prosthesis and compared with the total axial load application. The medial-lateral load distribution using the present method was found to be closer to the multibody dynamics prediction than the traditional total axial load application, and the maximum contact pressure and contact area were consistent with the corresponding load variation. The predicted total volumetric wear rate and area were similar between the two load applications. However, the split of the predicted wear volumes on the medial and the lateral sides was different. The lateral volumetric wear rate was 31.46% smaller than the medial from the traditional load application prediction, while from the medial-lateral load application, the lateral side was only 11.8% smaller than the medial. The medial-lateral load application could provide a new and more accurate method of load application for patient-specific preclinical contact mechanics and wear prediction of knee implants.

Development of a Subject-Specific Foot-Ground Contact Model for Walking

Computational walking simulations could facilitate the development of improved treatments for clinical conditions affecting walking ability. Since an effective treatment is likely to change a patient's foot-ground contact pattern and timing, such simulations should ideally utilize deformable foot-ground contact models tailored to the patient's foot anatomy and footwear. However, no study has reported a deformable modeling approach that can reproduce all six ground reaction quantities (expressed as three reaction force components, two center of pressure (CoP) coordinates, and a free reaction moment) for an individual subject during walking. This study proposes such an approach for use in predictive optimizations of walking. To minimize complexity, we modeled each foot as two rigid segments-a hindfoot (HF) segment and a forefoot (FF) segment-connected by a pin joint representing the toes flexion-extension axis. Ground reaction forces (GRFs) and moments acting on each segment were generated by a grid of linear springs with nonlinear damping and Coulomb friction spread across the bottom of each segment. The stiffness and damping of each spring and common friction parameter values for all springs were calibrated for both feet simultaneously via a novel three-stage optimization process that used motion capture and ground reaction data collected from a single walking trial. The sequential three-stage process involved matching (1) the vertical force component, (2) all three force components, and finally (3) all six ground reaction quantities. The calibrated model was tested using four additional walking trials excluded from calibration. With only small changes in input kinematics, the calibrated model reproduced all six ground reaction quantities closely (root mean square (RMS) errors less than 13 N for all three forces, 25 mm for anterior-posterior (AP) CoP, 8 mm for medial-lateral (ML) CoP, and 2 N·m for the free moment) for both feet in all walking trials. The largest errors in AP CoP occurred at the beginning and end of stance phase when the vertical ground reaction force (vGRF) was small. Subject-specific deformable foot-ground contact models created using this approach should enable changes in foot-ground contact pattern to be predicted accurately by gait optimization studies, which may lead to improvements in personalized rehabilitation medicine.

In Vivo Neuromechanics: Decoding Causal Motor Neuron Behavior with Resulting Musculoskeletal Function

Human motor function emerges from the interaction between the neuromuscular and the musculoskeletal systems. Despite the knowledge of the mechanisms underlying neural and mechanical functions, there is no relevant understanding of the neuro-mechanical interplay in the neuro-musculo-skeletal system. This currently represents the major challenge to the understanding of human movement. We address this challenge by proposing a paradigm for investigating spinal motor neuron contribution to skeletal joint mechanical function in the intact human in vivo. We employ multi-muscle spatial sampling and deconvolution of high-density fiber electrical activity to decode accurate α-motor neuron discharges across five lumbosacral segments in the human spinal cord. We use complete α-motor neuron discharge series to drive forward subject-specific models of the musculoskeletal system in open-loop with no corrective feedback. We perform validation tests where mechanical moments are estimated with no knowledge of reference data over unseen conditions. This enables accurate blinded estimation of ankle function purely from motor neuron information. Remarkably, this enables observing causal associations between spinal motor neuron activity and joint moment control. We provide a new class of neural data-driven musculoskeletal modeling formulations for bridging between movement neural and mechanical levels in vivo with implications for understanding motor physiology, pathology, and recovery.

Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation

Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading.

Reducing uncertainty when using knee-specific finite element models by assessing the effect of input parameters

Little is known about knee-specific factors that influence contact mechanics. Finite Element (FE) models offer a powerful tool to study contact mechanics, but there often exists ambiguity in the exact values of the inputs (e.g., tissue properties), which can result in a range of output values. Our objective was to quantify the reduction in the range of output values (defined herein as "uncertainty") from FE models of the human knee joint when known pre-defined values are used for clinically measurable inputs. To achieve this goal, we applied a statistically augmented FE approach to three human cadaveric knees for which full geometric and kinematic data were available. Two sets of conditions were simulated: All model inputs, clinically measurable or not, were varied to represent a "normal" patient population (Condition 1); subsets of clinically measurable variable inputs were fixed at specific values (called "patient derived inputs," or PDIs) while the other variables were varied over "normal" values (Condition 2). We found that by fixing body mass index and the anterior-posterior position of the meniscal-bony insertion points, model output uncertainty was reduced by one- to three-fifths. The magnitude of uncertainty reduction was strongly influenced by the individual knee. It was observed that knees with great anterior-posterior translation during gait had greater reductions in uncertainty when PDIs were used. This study represents the first step in developing FE models of the human knee joint based on inputs that can be derived from patients in a clinical setting. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2233-2242, 2017.

Relationships Between Tibiofemoral Contact Forces and Cartilage Morphology at 2 to 3 Years After Single-Bundle Hamstring Anterior Cruciate Ligament Reconstruction and in Healthy Knees

BACKGROUND

Prevention of knee osteoarthritis (OA) following anterior cruciate ligament (ACL) rupture and reconstruction is vital. Risk of postreconstruction knee OA is markedly increased by concurrent meniscal injury. It is unclear whether reconstruction results in normal relationships between tibiofemoral contact forces and cartilage morphology and whether meniscal injury modulates these relationships.

HYPOTHESES

Since patients with isolated reconstructions (ie, without meniscal injury) are at lower risk for knee OA, we predicted that relationships between tibiofemoral contact forces and cartilage morphology would be similar to those of normal, healthy knees 2 to 3 years postreconstruction. In knees with meniscal injuries, these relationships would be similar to those reported in patients with knee OA, reflecting early degenerative changes.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

Three groups were examined: (1) 62 patients who received single-bundle hamstring reconstruction with an intact, uninjured meniscus (mean age, 29.8 ± 6.4 years; mean weight, 74.9 ± 13.3 kg); (2) 38 patients with similar reconstruction with additional meniscal injury (ie, tear, repair) or partial resection (mean age, 30.6 ± 6.6 years; mean weight, 83.3 ± 14.3 kg); and (3) 30 ligament-normal, healthy individuals (mean age, 28.3 ± 5.2 years; mean weight, 74.9 ± 14.9 kg) serving as controls. All patients underwent magnetic resonance imaging to measure the medial and lateral tibial articular cartilage morphology (volumes and thicknesses). An electromyography-driven neuromusculoskeletal model determined medial and lateral tibiofemoral contact forces during walking. General linear models were used to assess relationships between tibiofemoral contact forces and cartilage morphology.

RESULTS

In control knees, cartilage was thicker compared with that of isolated and meniscal-injured ACL-reconstructed knees, while greater contact forces were related to both greater tibial cartilage volumes (medial: R² = 0.43, β = 0.62, P = .000; lateral: R² = 0.19, β = 0.46, P = .03) and medial thicknesses (R² = 0.24, β = 0.48, P = .01). In the overall group of ACL-reconstructed knees, greater contact forces were related to greater lateral cartilage volumes (R² = 0.08, β = 0.28, P = .01). In ACL-reconstructed knees with lateral meniscal injury, greater lateral contact forces were related to greater lateral cartilage volumes (R² = 0.41, β = 0.64, P = .001) and thicknesses (R² = 0.20, β = 0.46, P = .04).

CONCLUSION

At 2 to 3 years postsurgery, ACL-reconstructed knees had thinner cartilage compared with healthy knees, and there were no positive relationships between medial contact forces and cartilage morphology. In lateral meniscal-injured reconstructed knees, greater contact forces were related to greater lateral cartilage volumes and thicknesses, although it was unclear whether this was an adaptive response or associated with degeneration. Future clinical studies may seek to establish whether cartilage morphology can be modified through rehabilitation programs targeting contact forces directly in addition to the current rehabilitation foci of restoring passive and dynamic knee range of motion, knee strength, and functional performance.

Robust Real-Time Musculoskeletal Modeling Driven by Electromyograms

OBJECTIVE

Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human.

METHODS

We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system.

RESULTS

The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e., predicting accurate joint moments during six unseen tasks and one unseen DOF.

CONCLUSION

The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems.

SIGNIFICANCE

The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.

Muscle contributions to medial tibiofemoral compartment contact loading following ACL reconstruction using semitendinosus and gracilis tendon grafts

Background

The muscle-tendon properties of the semitendinosus (ST) and gracilis (GR) are substantially altered following tendon harvest for the purpose of anterior cruciate ligament reconstruction (ACLR). This study adopted a musculoskeletal modelling approach to determine how the changes to the ST and GR muscle-tendon properties alter their contribution to medial compartment contact loading within the tibiofemoral joint in post ACLR patients, and the extent to which other muscles compensate under the same external loading conditions during walking, running and sidestep cutting.

Materials and methods

Motion capture and electromyography (EMG) data from 16 lower extremity muscles were acquired during walking, running and cutting in 25 participants that had undergone an ACLR using a quadruple (ST+GR) hamstring auto-graft. An EMG-driven musculoskeletal model was used to estimate the medial compartment contact loads during the stance phase of each gait task. An adjusted model was then created by altering muscle-tendon properties for the ST and GR to reflect their reported changes following ACLR. Parameters for the other muscles in the model were calibrated to match the experimental joint moments.

Results

The medial compartment contact loads for the standard and adjusted models were similar. The combined contributions of ST and GR to medial compartment contact load in the adjusted model were reduced by 26%, 17% and 17% during walking, running and cutting, respectively. These deficits were balanced by increases in the contribution made by the semimembranosus muscle of 33% and 22% during running and cutting, respectively.

Conclusion

Alterations to the ST and GR muscle-tendon properties in ACLR patients resulted in reduced contribution to medial compartment contact loads during gait tasks, for which the semimembranosus muscle can compensate.

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.

Comparison of methodologies to assess muscle co-contraction during gait

The aim of this study was to compare co-contraction index (CCI) computed from muscle moments to different co-activation indexes (Co-Act) derived from EMG data at the ankle and the knee joint during gait. An EMG-driven model was used to estimate muscle moments during over-ground walking gait at a self-selected velocity from twelve healthy subjects. The CCI calculated from muscle moments was compared with three Co-Acts estimated from the normalized EMG data. The co-activation methods produced lower values than the CCI during the first double-support and the swing phase at the ankle joint and during the stance phase at the knee joint. The co-activation methods trend is to underestimate the simultaneous action of agonist and antagonist contraction. Because the EMG-driven model included the muscle mechanical properties (e.g. force-length-velocity relationship) and muscle moment-arm, the co-contraction based on major agonist and antagonist muscle moment may provide a more confident description of muscle action compared to co-activation indexes.

RIGID MUSCULOSKELETAL MODELS OF THE HUMAN BODY SYSTEMS: A REVIEW

Advancing the knowledge of the biomechanics of the human body is essential to improve the clinical decision-makings of musculoskeletal disorders in the framework of in silico medicine. An impressive number of research projects focused on the development of rigid-body musculoskeletal models have been conducted over the world thanks to the new research directives. However, the application of these models in clinical practices remains a challenging issue. The objective of this review paper was to present the most current rigid-body musculoskeletal models of the human body systems and to analyze their trends and weaknesses for clinical applications. Then, recommendations were proposed for future researches toward fully clinical decision support. A systematic review process was performed. Well-selected studies related to the most current rigid-body 3D musculoskeletal models for each body system component (jaw, cervical spine, upper limbs, lumbar spine, and lower limbs) were summarized and explored. Trends in rigid musculoskeletal modeling are highlighted as personalization, new imaging techniques for specific joint kinematics, and computational efficiency. Weaknesses are highlighted as modeling assumptions, use of generic model, lack of modeling consensus, model validation, and parameter and model uncertainties. Future directions related to joint and muscle modeling, neuro-musculoskeletal modeling, model validation, data and model uncertainty quantification are recommended.

Predictors of knee joint loading after anterior cruciate ligament reconstruction

Anterior cruciate ligament (ACL) injury results in altered knee joint mechanics which frequently continue even after ACL reconstruction. The persistence of altered mechanical loading of the knee is of concern due to its likely role in the development of post-traumatic osteoarthritis (OA). Joint contact forces are associated with post-traumatic OA development, but evaluation of factors influencing the magnitude of contact forces after ACL injury is needed to advance current strategies aimed at preventing post-traumatic OA. Therefore, the purpose of this study was to identify predictive factors of knee joint contact forces after ACL reconstruction. Thirty athletes completed standard gait analysis with surface electromyography 6 months after ACL reconstruction. An electromyographic-driven musculoskeletal model was used to estimate joint contact forces. External knee adduction moment was a significant predictor of medial compartment contact forces in both limbs, while vertical ground reaction force and co-contraction only contributed significantly in the uninvolved limb. The large influence of the knee adduction moment on joint contact forces provides mechanistic clues to understanding the mechanical pathway of post-traumatic OA after ACL injury. Statement of Clinical Significance: This study provides critical information in improving the understanding of mechanisms influencing the development of post-traumatic OA after ACL injury. Further work is needed to identify additional driving factors of joint loading in the ACL-injured limb and develop treatment strategies to avert the deleterious consequences of post-traumatic OA. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:651-656, 2017.

Accuracy of femur reconstruction from sparse geometric data using a statistical shape model

Sparse geometric information from limited field-of-view medical images is often used to reconstruct the femur in biomechanical models of the hip and knee. However, the full femur geometry is needed to establish boundary conditions such as muscle attachment sites and joint axes which define the orientation of joint loads. Statistical shape models have been used to estimate the geometry of the full femur from varying amounts of sparse geometric information. However, the effect that different amounts of sparse data have on reconstruction accuracy has not been systematically assessed. In this study, we compared shape model and linear scaling reconstruction of the full femur surface from varying proportions of proximal and distal partial femur geometry in combination with morphometric and landmark data. We quantified reconstruction error in terms of surface-to-surface error as well as deviations in the reconstructed femur's anatomical coordinate system which is important for biomechanical models. Using a partial proximal femur surface, mean shape model-based reconstruction surface error was 1.8 mm with 0.15° or less anatomic axis error, compared to 19.1 mm and 2.7-5.6° for linear scaling. Similar results were found when using a partial distal surface. However, varying amounts of proximal or distal partial surface data had a negligible effect on reconstruction accuracy. Our results show that given an appropriate set of sparse geometric data, a shape model can reconstruct full femur geometry with far greater accuracy than simple scaling.

Normalization influences knee abduction moment results: Could it influence ACL-injury research, too?

OBJECTIVES

Normalization of joint moments to reduce anthropometric influences prior to making group comparisons is a widely-accepted practice. However, a seminal prospective study reported greater non-normalized knee abduction moment (KAM) in nine females who subsequently sustained an ACL injury. It is not clear if this finding may have been influenced by the fact that the ACL-injured females were on average 3.6cm taller and 2.4kg heavier than uninjured females.

DESIGN

Cross-sectional.

METHODS

Peak KAM was identified in thirty-six females completing jump landings. A custom software program randomly divided participants into two groups that were compared on: (1) non-normalized KAM, (2) KAM normalized to body mass, and (3) KAM normalized to body height times weight a total of 500,000 times and the results categorically coded for statistical significance (α≤0.05). For the 10,591 iterations in which one group was 3-4cm taller and 2-3kg heavier, the agreement between results obtained using non-normalized versus normalized data were assessed using non-parametric analyses.

RESULTS

Despite moderate-strong agreement between the results obtained using non-normalized and normalized data (Κ=0.614-0.744), a significant effect of normalization on the interpretation of group differences in peak KAM was identified (p<0.001). In 30.4-41.9% of the cases in which non-normalized KAM was deemed significantly different between groups, no group differences were identified when using normalized KAM.

CONCLUSIONS

While it is unlikely the magnitude of the difference in non-normalized KAM identified prospectively in ACL-injured females was attributable solely to anthropometric differences, caution should be exercised when evaluating research findings reporting non-normalized KAM.

The Influence of Component Alignment and Ligament Properties on Tibiofemoral Contact Forces in Total Knee Replacement

The study objective was to investigate the influence of coronal plane alignment and ligament properties on total knee replacement (TKR) contact loads during walking. We created a subject-specific knee model of an 83-year-old male who had an instrumented TKR. The knee model was incorporated into a lower extremity musculoskeletal model and included deformable contact, ligamentous structures, and six degrees-of-freedom (DOF) tibiofemoral and patellofemoral joints. A novel numerical optimization technique was used to simultaneously predict muscle forces, secondary knee kinematics, ligament forces, and joint contact pressures from standard gait analysis data collected on the subject. The nominal knee model predictions of medial, lateral, and total contact forces during gait agreed well with TKR measures, with root-mean-square (rms) errors of 0.23, 0.22, and 0.33 body weight (BW), respectively. Coronal plane component alignment did not affect total knee contact loads, but did alter the medial-lateral load distribution, with 4 deg varus and 4 deg valgus rotations in component alignment inducing +17% and -23% changes in the first peak medial tibiofemoral contact forces, respectively. A Monte Carlo analysis showed that uncertainties in ligament stiffness and reference strains induce ±0.2 BW uncertainty in tibiofemoral force estimates over the gait cycle. Ligament properties had substantial influence on the TKR load distributions, with the medial collateral ligament and iliotibial band (ITB) properties having the largest effects on medial and lateral compartment loading, respectively. The computational framework provides a viable approach for virtually designing TKR components, considering parametric uncertainty and predicting the effects of joint alignment and soft tissue balancing procedures on TKR function during movement.

Influence of the Level of Muscular Redundancy on the Validity of a Musculoskeletal Model

While recent literature has clearly demonstrated that an extensive personalization of the musculoskeletal models was necessary to reach high accuracy, several components of the generic models may be further investigated before defining subject-specific parameters. Among others, the choice in muscular geometry and thus the level of muscular redundancy in the model may have a noticeable influence on the predicted musculotendon and joint contact forces. In this context, the aim of this study was to investigate if the level of muscular redundancy can contribute or not to reduce inaccuracies in tibiofemoral contact forces predictions. For that, the dataset disseminated through the Sixth Grand Challenge Competition to Predict In Vivo Knee Loads was applied to a versatile 3D lower limb musculoskeletal model in which two muscular geometries (i.e., two different levels of muscular redundancy) were implemented. This dataset provides tibiofemoral implant measurements for both medial and lateral compartments and thus allows evaluation of the validity of the model predictions. The results suggest that an increase of the level of muscular redundancy corresponds to a better accuracy of total tibiofemoral contact force whatever the gait pattern investigated. However, the medial and lateral contact forces ratio and accuracy were not necessarily improved when increasing the level of muscular redundancy and may thus be attributed to other parameters such as the location of contact points. To conclude, the muscular geometry, among other components of the generic model, has a noticeable impact on joint contact forces predictions and may thus be correctly chosen even before trying to personalize the model.

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.

Tibiofemoral contact forces during walking, running and sidestepping

We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20<Radj(2)<0.78), but were variable across gait tasks. Step-wise regression equations from a particular gait task (e.g. walking) produced large errors when applied to a different gait task (e.g. running or sidestepping). Muscles well stabilized the knee, increasing their role in stabilization from walking to running to sidestepping. KAM was a poor predictor of medial contact force and load distributions. Step-wise regression models results suggest the relationships between external gait measures and contact forces cannot be generalized across tasks. Neuromusculoskeletal modelling may be required to examine tibiofemoral contact forces and role of muscle in knee stabilization across gait tasks.

A method for concise reporting of joint reaction forces orientation during gait

Estimation of joint reaction forces (JRF) is critical for the understanding of load-related pathologies, such as osteoarthritis (OA). Typically, singular components at discrete time-points are presented without knowledge of their orientation over time. The aim of this study was to develop and demonstrate the utility of a method for the concise and intuitive representation of JRF orientation. A scaled musculoskeletal model of the lower limbs was informed by walking gait data from adults with knee OA (n=10) and healthy controls (C) (n=10). Muscle forces and subsequently JRF were computed. The intersections of the JRF vector and a transverse plane proximal to the joint were computed. The 95% confidence ellipse was computed for these points. This allowed the following metrics to be calculated: the normalised area of the ellipse (A); the ratio of the long and short axes (R); the angle between the long axis of the ellipse and the anterior-posterior axis of the distal segment (α) and the position of the centre of the ellipse relative to the origin of the segment (X_C, Z_C). At the knee, the OA group displayed a more AP-oriented JRF (OA: α=3.0±28.2°C: α=-15.3±37.1°, p= 0.03), less overall variation in the JRF orientation (OA: A=0.04±0.03C: A=0.07±0.03, p<0.001), and less ML fluctuations of the JRF (OA: R=4.17±3.48C: R=2.41±0.76, p=0.01). Significant effects were also observed at the hip and ankle. The method presented has the potential to allow better visualisation and insight into the behaviour of joint contact forces in clinically relevant pathologies.

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.

Surgical Simulations Based on Limited Quantitative Data: Understanding How Musculoskeletal Models Can Be Used to Predict Moment Arms and Guide Experimental Design

The utility of biomechanical models and simulations to examine clinical problems is currently limited by the need for extensive amounts of experimental data describing how a given procedure or disease affects the musculoskeletal system. Methods capable of predicting how individual biomechanical parameters are altered by surgery are necessary for the efficient development of surgical simulations. In this study, we evaluate to what extent models based on limited amounts of quantitative data can be used to predict how surgery influences muscle moment arms, a critical parameter that defines how muscle force is transformed into joint torque. We specifically examine proximal row carpectomy and scaphoid-excision four-corner fusion, two common surgeries to treat wrist osteoarthritis. Using models of these surgeries, which are based on limited data and many assumptions, we perform simulations to formulate a hypothesis regarding how these wrist surgeries influence muscle moment arms. Importantly, the hypothesis is based on analysis of only the primary wrist muscles. We then test the simulation-based hypothesis using a cadaveric experiment that measures moment arms of both the primary wrist and extrinsic thumb muscles. The measured moment arms of the primary wrist muscles are used to verify the hypothesis, while those of the extrinsic thumb muscles are used as cross-validation to test whether the hypothesis is generalizable. The moment arms estimated by the models and measured in the cadaveric experiment both indicate that a critical difference between the surgeries is how they alter radial-ulnar deviation versus flexion-extension moment arms at the wrist. Thus, our results demonstrate that models based on limited quantitative data can provide novel insights. This work also highlights that synergistically utilizing simulation and experimental methods can aid the design of experiments and make it possible to test the predictive limits of current computer simulation techniques.

Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling

This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.

Neural Data-Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies

OBJECTIVES

The development of neurorehabilitation technologies requires the profound understanding of the mechanisms underlying an individual's motor ability and impairment. A major factor limiting this understanding is the difficulty of bridging between events taking place at the neurophysiologic level (i.e., motor neuron firings) with those emerging at the musculoskeletal level (i.e. joint actuation), in vivo in the intact moving human. This review presents emerging model-based methodologies for filling this gap that are promising for developing clinically viable technologies.

METHODS

We provide a design overview of musculoskeletal modeling formulations driven by recordings of neuromuscular activity with a critical comparison to alternative model-free approaches in the context of neurorehabilitation technologies. We present advanced electromyography-based techniques for interfacing with the human nervous system and model-based techniques for translating the extracted neural information into estimates of motor function.

RESULTS

We introduce representative application areas where modeling is relevant for accessing neuromuscular variables that could not be measured experimentally. We then show how these variables are used for designing personalized rehabilitation interventions, biologically inspired limbs, and human-machine interfaces.

CONCLUSION

The ability of using electrophysiological recordings to inform biomechanical models enables accessing a broader range of neuromechanical variables than analyzing electrophysiological data or movement data individually. This enables understanding the neuromechanical interplay underlying in vivo movement function, pathology, and robot-assisted motor recovery.

SIGNIFICANCE

Filling the gap between our understandings of movement neural and mechanical functions is central for addressing one of the major challenges in neurorehabilitation: personalizing current technologies and interventions to an individual's anatomy and impairment.

Influence of Ligament Properties on Tibiofemoral Mechanics in Walking

Computational knee models provide a powerful platform to investigate the effects of injury and surgery on functional knee behavior. The objective of this study was to use a multibody knee model to investigate the influence of ligament properties on tibiofemoral kinematics and cartilage contact pressures in the stance phase of walking. The knee model included 14 ligament bundles and articular cartilage contact acting across the tibiofemoral and patellofemoral joints. The knee was incorporated into a lower extremity musculoskeletal model and was used to simulate knee mechanics during the stance phase of normal walking. A Monte Carlo approach was employed to assess the influence of ligament stiffness and reference strain on knee mechanics. The anterior cruciate ligament (ACL), medial collateral ligament (MCL), and posterior capsule properties exhibited significant influence on anterior tibial translation at heel strike, with the ACL acting as the primary restraint to anterior translation in mid-stance. The MCL and lateral collateral ligament (LCL) exhibited the greatest influence on tibial rotation from heel strike through mid-stance. Simulated tibial plateau contact location was dependent on the ACL, MCL, and LCL properties, while pressure magnitudes were most dependent on the ACL. A decrease in ACL stiffness or reference strain significantly increased the average contact pressure in mid-stance, with the pressure migrating posteriorly on the medial tibial plateau. These ligament-dependent shifts in tibiofemoral cartilage contact during walking are potentially relevant to consider when investigating the causes of early-onset osteoarthritis following knee ligament injury and surgical treatment.

In Vivo Knee Contact Force Prediction Using Patient-Specific Musculoskeletal Geometry in a Segment-Based Computational Model

Segment-based musculoskeletal models allow the prediction of muscle, ligament, and joint forces without making assumptions regarding joint degrees-of-freedom (DOF). The dataset published for the “Grand Challenge Competition to Predict in vivo Knee Loads” provides directly measured tibiofemoral contact forces for activities of daily living (ADL). For the Sixth Grand Challenge Competition to Predict in vivo Knee Loads, blinded results for “smooth” and “bouncy” gait trials were predicted using a customized patient-specific musculoskeletal model. For an unblinded comparison, the following modifications were made to improve the predictions: further customizations, including modifications to the knee center of rotation; reductions to the maximum allowable muscle forces to represent known loss of strength in knee arthroplasty patients; and a kinematic constraint to the hip joint to address the sensitivity of the segment-based approach to motion tracking artifact. For validation, the improved model was applied to normal gait, squat, and sit-to-stand for three subjects. Comparisons of the predictions with measured contact forces showed that segment-based musculoskeletal models using patient-specific input data can estimate tibiofemoral contact forces with root mean square errors (RMSEs) of 0.48–0.65 times body weight (BW) for normal gait trials. Comparisons between measured and predicted tibiofemoral contact forces yielded an average coefficient of determination of 0.81 and RMSEs of 0.46–1.01 times BW for squatting and 0.70–0.99 times BW for sit-to-stand tasks. This is comparable to the best validations in the literature using alternative models.

Pediatric obesity and walking duration increase medial tibiofemoral compartment contact forces

With the high prevalence of pediatric obesity there is a need for structured physical activity during childhood. However, altered tibiofemoral loading during physical activity in obese children likely contribute to their increased risk of orthopedic disorders of the knee. The goal of this study was to determine the effects of pediatric obesity and walking duration on medial and lateral tibiofemoral contact forces. We collected experimental biomechanics data during treadmill walking at 1 m•s(-1) for 20 min in 10 obese and 10 healthy-weight 8-12 year-olds. We created subject-specific musculoskeletal models using radiographic measures of tibiofemoral alignment and centers-of-pressure, and predicted medial and lateral tibiofemoral contact forces at the beginning and end of each trial. Obesity and walking duration affected tibiofemoral loading. At the beginning of the trail, the average percent of the total load passing through the medial compartment during stance was 85% in the obese children and 63% in the healthy-weight children; at the end of the trial, the medial distribution was 90% in the obese children and 72% in the healthy-weight children. Medial compartment loading rates were 1.78 times greater in the obese participants. The medial compartment loading rate increased 17% in both groups at the end compared to the beginning of the trial (p = 0.001). We found a strong linear relationship between body-fat percentage and the medial-lateral load distribution (r(2) = 0.79). Altered tibiofemoral loading during walking in obese children may contribute to their increased risk of knee pain and pathology.

Musculoskeletal Simulation for Assessment of Effect of Movement-Based Structure-Modifying Treatment Strategies

The better understanding of the complex mechanism between neural motor control and its resulting joint kinematics and muscle forces allows a better elucidation of the mechanisms behind body growth, aging progression, and disease development. This study aimed at investigating the impact of movement-based structure-modifying treatment strategies on joint kinematics, muscle forces, and muscle synergies of the gait with instrumented implant. A patient-specific musculoskeletal model was used to quantitatively assess the deviations of joint and muscle behaviors between the normal gait and 4 gait modifications (bouncy, medial thrust, midcrouch, and mtp (i.e., gait with forefoot strike)). Moreover, muscle synergy analysis was performed using EMG-based nonnegative matrix factorization. Large variation of 19 degrees and 190 N was found for knee flexion/extension and lower limb muscle forces, respectively. EMG-based muscle synergy analysis revealed that the activation levels of the vastus lateralis and tibialis anterior are dominant for the midcrouch gait. In addition, an important contribution of semimembranosus to the medial thrust and midcrouch gaits was also observed. In fact, such useful information could allow a better understanding of the joint function and muscle synergy strategies leading to deeper knowledge of joint and muscle mechanisms related to neural voluntary motor commands.

Alterations in knee contact forces and centers in stance phase of gait: A detailed lower extremity musculoskeletal model

Evaluation of contact forces-centers of the tibiofemoral joint in gait has crucial biomechanical and pathological consequences. It involves however difficulties and limitations in in vitro cadaver and in vivo imaging studies. The goal is to estimate total contact forces (CF) and location of contact centers (CC) on the medial and lateral plateaus using results computed by a validated finite element model simulating the stance phase of gait for normal as well as osteoarthritis, varus-valgus and posterior tibial slope altered subjects. Using foregoing contact results, six methods commonly used in the literature are also applied to estimate and compare locations of CC at 6 periods of stance phase (0%, 5%, 25%, 50%, 75% and 100%). TF joint contact forces are greater on the lateral plateau very early in stance and on the medial plateau thereafter during 25-100% stance periods. Large excursions in the location of CC (>17mm), especially on the medial plateau in the mediolateral direction, are computed. Various reported models estimate quite different CCs with much greater variations (~15mm) in the mediolateral direction on both plateaus. Compared to our accurately computed CCs taken as the gold standard, the centroid of contact area algorithm yielded least differences (except in the mediolateral direction on the medial plateau at ~5mm) whereas the contact point and weighted center of proximity algorithms resulted overall in greatest differences. Large movements in the location of CC should be considered when attempting to estimate TF compartmental contact forces in gait.