Subject-specific calibration of neuromuscular parameters enables neuromusculoskeletal models to estimate physiologically plausible hip joint contact forces in healthy adults

In-vivo hip joint contact forces (HJCF) can be estimated using computational neuromusculoskeletal (NMS) modelling. However, different neural solutions can result in different HJCF estimations. NMS model predictions are also influenced by the selection of neuromuscular parameters, which are either based on cadaveric data or calibrated to the individual. To date, the best combination of neural solution and parameter calibration to obtain plausible estimations of HJCF have not been identified. The aim of this study was to determine the effect of three electromyography (EMG)-informed neural solution modes (EMG-driven, EMG-hybrid, and EMG-assisted) and static optimisation, each using three different parameter calibrations (uncalibrated, minimise joint moments error, and minimise joint moments error and peak HJCF), on the estimation of HJCF in a healthy population (n = 23) during walking. When compared to existing in-vivo data, the EMG-assisted mode and static optimisation produced the most physiologically plausible HJCF when using a NMS model calibrated to minimise joint moments error and peak HJCF. EMG-assisted mode produced first and second peaks of 3.55 times body weight (BW) and 3.97 BW during walking; static optimisation produced 3.75 BW and 4.19 BW, respectively. However, compared to static optimisation, EMG-assisted mode generated muscle excitations closer to recorded EMG signals (average across hip muscles R² = 0.60 ± 0.37 versus R² = 0.12 ± 0.14). Findings suggest that the EMG-assisted mode combined with minimise joint moments error and peak HJCF calibration is preferable for the estimation of HJCF and generation of realistic load distribution across muscles.     

An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo

This paper examined if an electromyography (EMG) driven musculoskeletal model of the human knee could be used to predict knee moments, calculated using inverse dynamics, across a varied range of dynamic contractile conditions. Muscle-tendon lengths and moment arms of 13 muscles crossing the knee joint were determined from joint kinematics using a three-dimensional anatomical model of the lower limb. Muscle activation was determined using a second-order discrete non-linear model using rectified and low-pass filtered EMG as input. A modified Hill-type muscle model was used to calculate individual muscle forces using activation and muscle tendon lengths as inputs. The model was calibrated to six individuals by altering a set of physiologically based parameters using mathematical optimisation to match the net flexion/extension (FE) muscle moment with those measured by inverse dynamics. The model was calibrated for each subject using 5 different tasks, including passive and active FE in an isokinetic dynamometer, running, and cutting manoeuvres recorded using three-dimensional motion analysis. Once calibrated, the model was used to predict the FE moments, estimated via inverse dynamics, from over 200 isokinetic dynamometer, running and sidestepping tasks. The inverse dynamics joint moments were predicted with an average R(2) of 0.91 and mean residual error of approximately 12 Nm. A re-calibration of only the EMG-to-activation parameters revealed FE moments prediction across weeks of similar accuracy. Changing the muscle model to one that is more physiologically correct produced better predictions. The modelling method presented represents a good way to estimate in vivo muscle forces during movement tasks.     

Three-dimensional knee joint contact forces during walking in unilateral transtibial amputees

Individuals with unilateral transtibial amputations have greater prevalence of osteoarthritis in the intact knee joint relative to the residual leg and non-amputees, but the cause of this greater prevalence is unclear. The purpose of this study was to compare knee joint contact forces and the muscles contributing to these forces between amputees and non-amputees during walking using forward dynamics simulations. We predicted that the intact knee contact forces would be higher than those of the residual leg and non-amputees. In the axial and mediolateral directions, the intact and non-amputee legs had greater peak tibio-femoral contact forces and impulses relative to the residual leg. The peak axial contact force was greater in the intact leg relative to the non-amputee leg, but the stance phase impulse was greater in the non-amputee leg. The vasti and hamstrings muscles in early stance and gastrocnemius in late stance were the largest contributors to the joint contact forces in the non-amputee and intact legs. Through dynamic coupling, the soleus and gluteus medius also had large contributions, even though they do not span the knee joint. In the residual leg, the prosthesis had large contributions to the joint forces, similar to the soleus in the intact and non-amputee legs. These results identify the muscles that contribute to knee joint contact forces during transtibial amputee walking and suggest that the peak knee contact forces may be more important than the knee contact impulses in explaining the high prevalence of intact leg osteoarthritis.     

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

Estimating tibiofemoral joint contact forces is important for understanding the initiation and progression of knee osteoarthritis. However, tibiofemoral contact force predictions are influenced by many factors including muscle forces and anatomical representations of the knee joint. This study aimed to investigate the influence of subject-specific geometry and knee joint kinematics on the prediction of tibiofemoral contact forces using a calibrated EMG-driven neuromusculoskeletal model of the knee. One participant fitted with an instrumented total knee replacement walked at a self-selected speed while medial and lateral tibiofemoral contact forces, ground reaction forces, whole-body kinematics, and lower-limb muscle activity were simultaneously measured. The combination of generic and subject-specific knee joint geometry and kinematics resulted in four different OpenSim models used to estimate muscle–tendon lengths and moment arms. The subject-specific geometric model was created from CT scans and the subject-specific knee joint kinematics representing the translation of the tibia relative to the femur was obtained from fluoroscopy. The EMG-driven model was calibrated using one walking trial, but with three different cost functions that tracked the knee flexion/extension moments with and without constraint over the estimated joint contact forces. The calibrated models then predicted the medial and lateral tibiofemoral contact forces for five other different walking trials. The use of subject-specific models with minimization of the peak tibiofemoral contact forces improved the accuracy of medial contact forces by 47% and lateral contact forces by 7%, respectively compared with the use of generic musculoskeletal model.     

Tibio-femoral joint contact forces in sheep

Although the sheep has become a standard model for understanding the mechanical conditions that occur after injury and investigating surgical treatments such as osteochondral defect healing and ligament reconstruction, no study has yet evaluated the contact forces that occur in the sheep tibio-femoral joint in vivo. In this study, bone pins, together with reflective markers, were used to measure the 3D kinematics of three sheep hind limbs, simultaneously with the ground reaction forces during repetitions of gait trials. Joint contact forces were then calculated using inverse dynamics and optimisation techniques. Whilst average peak axial tibio-femoral contact forces of 2.1 body weight (BW) were calculated across the 3 sheep, only small medio-lateral and antero-posterior shear forces, averaging 0.7 BW, were determined. Average knee flexion angles ranging from 49 degrees to 70 degrees were observed. From the forces determined in this study, we have provided a better understanding of the mechanical loading environment that occurs in sheep. This has important implications for the interpretation of knee studies in quadrupeds and their relevance to the clinical situation.     

A calibrated EMG-informed neuromusculoskeletal model can appropriately account for muscle co-contraction in the estimation of hip joint contact forces in people with hip osteoarthritis

Abnormal hip joint contact forces (HJCF) are considered a primary mechanical contributor to the progression of hip osteoarthritis (OA). Compared to healthy controls, people with hip OA often present with altered muscle activation patterns and greater muscle co-contraction, both of which can influence HJCF. Neuromusculoskeletal (NMS) modelling is non-invasive approach to estimating HJCF, whereby different neural control solutions can be used to estimate muscle forces. Static optimisation, available within the popular NMS modelling software OpenSim, is a commonly used neural control solution, but may not account for an individual’s unique muscle activation patterns and/or co-contraction that are often evident in pathological population. Alternatively, electromyography (EMG)-assisted neural control solutions, available within CEINMS software, have been shown to account for individual activation patterns in healthy people. Nonetheless, their application in people with hip OA, with conceivably greater levels of co-contraction, is yet to be explored. The aim of this study was to compare HJCF estimations using static optimisation (in OpenSim) and EMG-assisted (in CEINMS) neural control solutions during walking in people with hip OA. EMG-assisted neural control solution was more consistent with both EMG and joint moment data than static optimisation, and also predicted significantly higher HJCF peaks (p < 0.001). The EMG-assisted neural control solution also accounted for more muscle co-contraction than static optimisation (p = 0.03), which probably contributed to these higher HJCF peaks. Findings suggest that the EMG-assisted neural control solution may estimate more physiologically plausible HJCF than static optimisation in a population with high levels of co-contraction, such as hip OA.     

A method of calculating physiologically relevant joint reaction forces during forward dynamic simulations of movement from an existing knee model

In the commonly used SIMM software, which includes a complete musculoskeletal model of the lower limbs, the reaction forces at the knee are computed. These reaction forces represent the bone-on-bone contact forces and the soft tissue forces (e.g. ligaments) other than muscles acting at the joint. In the knee model integrated into this software, a patellotibial joint rather than a patellofemoral joint is defined, and a force acting along the direction of the patellar ligament is not included. Although this knee model results in valid kinematics and muscle moment arms, the reaction forces at the knee calculated do not represent physiologic knee joint reaction forces. Hence our objectives were to develop a method of calculating physiologic knee joint reaction forces using the knee model incorporated into the SIMM software and to demonstrate the differences in the forces returned by SIMM and the physiologic forces in an example. Our method converts the anatomically fictional patellotibial joint into a patellofemoral joint and computes the force in an inextensible patellar ligament. In our example, the rectus femoris was fully excited isometrically, with the knee and hip flexed to 90 degrees . The resulting SIMM tibiofemoral joint reaction force was primarily shear, because the quadriceps force was applied to the tibia via the fictional patellotibial joint. In contrast the physiologic tibiofemoral joint reaction force was primarily compression, because the quadriceps force was applied through the patellar ligament. This result illustrates that the physiologic knee joint reaction forces are profoundly different than the forces returned by SIMM. However physiologic knee joint reaction forces can be computed with postprocessing of SIMM results.     

Sensitivity of tibio-menisco-femoral joint contact behavior to variations in knee kinematics

Use of computational models with kinematic boundary conditions to study the knee joint contact behavior for normal and pathologic knee joints depends on an understanding of the impacts of kinematic uncertainty. We studied the sensitivities of tibio-menisco-femoral joint contact behavior to variations in knee kinematics using a finite element model (FEM) with geometry and kinematic boundary conditions derived from sequences of magnetic resonance (MR) images. The MR images were taken before and after axial compression was applied to the knee joint of a healthy subject. A design of experiments approach was used to study the impact of the variation in knee kinematics on the contact outputs. We also explored the feasibility of using supplementary hip images to improve the accuracy of knee kinematics. Variations in knee kinematics (0.25mm in medial-lateral, 0.1mm in anterior-posterior and superior-inferior translations, and 0.1 degrees in flexion-extension and varus-valgus, 0.25 degrees in external-internal rotations) caused large variations in joint contact behavior. When kinematic boundary conditions resulted in close approximations of the model-predicted joint contact force to the applied force, variations in predictions of contact parameters were also reduced. The combination of inferior-superior and medial-lateral translations accounted for over 70% of variations for all the contact parameters examined. The inclusion of hip images in kinematic calculations improved knee kinematics by matching the femoral head position. Our findings demonstrate the importance of improving the accuracy and precision of knee kinematic measurements, especially when utilized as an input for finite element models.     

Tibiofemoral joint contact force in deep knee flexion and its consideration in knee osteoarthritis and joint replacement

The aim of the study was to estimate the tibiofemoral joint force in deep flexion to consider how the mechanical load affects the knee. We hypothesize that the joint force should not become sufficiently large to damage the joint under normal contact area, but should become deleterious to the joint under the limited contact area. Sixteen healthy knees were analyzed using a motion capture system, a force plate, a surface electromyography, and a knee model, and then tibiofemoral joint contact forces were calculated. Also, a contact stress simulation using the contact areas from the literature was performed. The peak joint contact forces (M +/- SD) were 4566 +/- 1932 N at 140 degrees in rising from full squat and 4479 +/- 1478 N at 90 degrees in rising from kneeling. Under normal contact area, the tibiofemoral contact stresses in deep flexion were less than 5 MPa and did not exceed the stress to damage the cartilage. The contact stress simulation suggests that knee prosthesis having the contact area smaller than 200 mm2 may be problematic since the contact stress in deep flexion would become larger than 21 MPa, and it would lead damage or wear of the polyethylene.     

In vivo contact kinematics and contact forces of the knee after total knee arthroplasty during dynamic weight-bearing activities

Analysis of polyethylene component wear and implant loosening in total knee arthroplasty (TKA) requires precise knowledge of in vivo articular motion and loading conditions. This study presents a simultaneous in vivo measurement of tibiofemoral articular contact forces and contact kinematics in three TKA patients. These measurements were accomplished via a dual fluoroscopic imaging system and instrumented tibial implants, during dynamic single leg lunge and chair rising-sitting. The measured forces and contact locations were also used to determine mediolateral distribution of axial contact forces. Contact kinematics data showed a medial pivot during flexion of the knee, for all patients in the study. Average axial forces were higher for lunge compared to chair rising-sitting (224% vs. 187% body weight). In this study, we measured peak anteroposterior and mediolateral forces averaging 13.3% BW during lunge and 18.5% BW during chair rising-sitting. Mediolateral distributions of axial contact force were both patient and activity specific. All patients showed equitable medial-lateral loading during lunge but greater loads at the lateral compartment during chair rising-sitting. The results of this study may enable more accurate reproduction of in vivo loads and articular motion patterns in wear simulators and finite element models. This in turn may help advance our understanding of factors limiting longevity of TKA implants, such as aseptic loosening and polyethylene component wear, and enable improved TKA designs.     

Simultaneous prediction of muscle and contact forces in the knee during gait

Musculoskeletal models are currently the primary means for estimating in vivo muscle and contact forces in the knee during gait. These models typically couple a dynamic skeletal model with individual muscle models but rarely include articular contact models due to their high computational cost. This study evaluates a novel method for predicting muscle and contact forces simultaneously in the knee during gait. The method utilizes a 12 degree-of-freedom knee model (femur, tibia, and patella) combining muscle, articular contact, and dynamic skeletal models. Eight static optimization problems were formulated using two cost functions (one based on muscle activations and one based on contact forces) and four constraints sets (each composed of different combinations of inverse dynamic loads). The estimated muscle and contact forces were evaluated using in vivo tibial contact force data collected from a patient with a force-measuring knee implant. When the eight optimization problems were solved with added constraints to match the in vivo contact force measurements, root-mean-square errors in predicted contact forces were less than 10 N. Furthermore, muscle and patellar contact forces predicted by the two cost functions became more similar as more inverse dynamic loads were used as constraints. When the contact force constraints were removed, estimated medial contact forces were similar and lateral contact forces lower in magnitude compared to measured contact forces, with estimated muscle forces being sensitive and estimated patellar contact forces relatively insensitive to the choice of cost function and constraint set. These results suggest that optimization problem formulation coupled with knee model complexity can significantly affect predicted muscle and contact forces in the knee during gait. Further research using a complete lower limb model is needed to assess the importance of this finding to the muscle and contact force estimation process.     

Computational biodynamics of human knee joint in gait: from muscle forces to cartilage stresses

Using a validated finite element model of the intact knee joint we aim to compute muscle forces and joint response in the stance phase of gait. The model is driven by reported in vivo kinematics-kinetics data and ground reaction forces in asymptomatic subjects. Cartilage layers and menisci are simulated as depth-dependent tissues with collagen fibril networks. A simplified model with less refined mesh and isotropic depth-independent cartilage is also considered to investigate the effect of model accuracy on results. Muscle forces and joint detailed response are computed following an iterative procedure yielding results that satisfy kinematics/kinetics constraints while accounting at deformed configurations for muscle forces and passive properties. Predictions confirm that muscle forces and joint response alter substantially during the stance phase and that a simplified joint model may accurately be used to estimate muscle forces but not necessarily contact forces/areas, tissue stresses/strains, and ligament forces. Predictions are in general agreement with results of earlier studies. Performing the analyses at 6 periods from beginning to the end (0%, 5%, 25%, 50%, 75% and 100%), hamstrings forces peaked at 5%, quadriceps forces at 25% whereas gastrocnemius forces at 75%. ACL Force reached its maximum of 343 N at 25% and decreased thereafter. Contact forces reached maximum at 5%, 25% and 75% periods with the medial compartment carrying a major portion of load and experiencing larger relative movements and cartilage strains. Much smaller contact stresses were computed at the patellofemoral joint. This novel iterative kinematics-driven model is promising for the joint analysis in altered conditions.     

Effect of knee joint flexion and femur rotation on retropatellar contact of the human knee joint]

The aim of the present study was to evaluate retropatellar contact characteristics at different angles of flexion of the knee joint. To this end, 6 cadaveric legs were examined using pressure sensitive film (Fuji Prescale type "super low") at angles of flexion of 45 degrees, 60 degrees, 90 degrees and 120 degrees both in neutral rotation and 10 degrees internal and external rotation of the femur in the same knee joints. A force of 140 N was applied to both the vastus medialis and lateralis, and a comparison made with a medially and a laterally dominating muscle force. The contact areas decreased with increasing angles of flexion. The medially dominating muscle traction increased the contact area. Comparison between internal and external rotation revealed a decrease in contact area on internal rotation. The pressure measurements were comparable in all loading situations. Comparison between neutral and medial traction revealed significant differences in contact area, pressure and force. The influence of femoral rotation showed no significant difference. A comparison of the different angles of flexion revealed only few significant differences. To prevent the development of retropatellar arthrosis, maximum contact areas are necessary. The study has shown an advantage for medially dominating muscle traction, and external rotation of the femur.     

Influence of altered gait patterns on the hip joint contact forces

Children who exhibit gait deviations often present a range of bone deformities, particularly at the proximal femur. Altered gait may affect bone growth and lead to deformities by exerting abnormal stresses on the developing bones. The objective of this study was to calculate variations in the hip joint contact forces with different gait patterns. Muscle and hip joint contact forces of four children with different walking characteristics were calculated using an inverse dynamic analysis and a static optimisation algorithm. Kinematic and kinetic analyses were based on a generic musculoskeletal model scaled down to accommodate the dimensions of each child. Results showed that for all the children with altered gaits both the orientation and magnitude of the hip joint contact force deviated from normal. The child with the most severe gait deviations had hip joint contact forces 30% greater than normal, most likely due to the increase in muscle forces required to sustain his crouched stance. Determining how altered gait affects joint loading may help in planning treatment strategies to preserve correct loading on the bone from a young age.     

Individual muscle contributions to the axial knee joint contact force during normal walking

Muscles are significant contributors to the high joint forces developed in the knee during human walking. Not only do muscles contribute to the knee joint forces by acting to compress the joint, but they also develop joint forces indirectly through their contributions to the ground reaction forces via dynamic coupling. Thus, muscles can have significant contributions to forces at joints they do not span. However, few studies have investigated how the major lower-limb muscles contribute to the knee joint contact forces during walking. The goal of this study was to use a muscle-actuated forward dynamics simulation of walking to identify how individual muscles contribute to the axial tibio-femoral joint force. The simulation results showed that the vastii muscles are the primary contributors to the axial joint force in early stance while the gastrocnemius is the primary contributor in late stance. The tibio-femoral joint force generated by these muscles was at times greater than the muscle forces themselves. Muscles that do not cross the knee joint (e.g., the gluteus maximus and soleus) also have significant contributions to the tibio-femoral joint force through their contributions to the ground reaction forces. Further, small changes in walking kinematics (e.g., knee flexion angle) can have a significant effect on the magnitude of the knee joint forces. Thus, altering walking mechanics and muscle coordination patterns to utilize muscle groups that perform the same biomechanical function, yet contribute less to the knee joint forces may be an effective way to reduce knee joint loading during walking.     

Muscle and external load contribution to knee joint contact loads during normal gait

Large knee adduction moments during gait have been implicated as a mechanical factor related to the progression and severity of tibiofemoral osteoarthritis and it has been proposed that these moments increase the load on the medial compartment of the knee joint. However, this mechanism cannot be validated without taking into account the internal forces and moments generated by the muscles and ligaments, which cannot be easily measured. Previous musculoskeletal models suggest that the medial compartment of the tibiofemoral joint bears the majority of the tibiofemoral load, with the lateral compartment unloaded at times during stance. Yet these models did not utilise explicitly measured muscle activation patterns and measurements from an instrumented prosthesis which do not portray lateral compartment unloading. This paper utilised an EMG-driven model to estimate muscle forces and knee joint contact forces during healthy gait. Results indicate that while the medial compartment does bear the majority of the load during stance, muscles provide sufficient stability to counter the tendency of the external adduction moment to unload the lateral compartment. This stability was predominantly provided by the quadriceps, hamstrings, and gastrocnemii muscles, although the contribution from the tensor fascia latae was also significant. Lateral compartment unloading was not predicted by the EMG-driven model, suggesting that muscle activity patterns provide useful input to estimate muscle and joint contact forces.     

Protocol for constructing subject-specific biomechanical models of knee joint

A robust protocol for building subject-specific biomechanical models of the human knee joint is proposed which uses magnetic resonance imaging, motion analysis and force platform data in conjunction with detailed 3D finite element models. The proposed protocol can be used for determining stress and strain distributions and contact kinetics in different knee elements at different body postures during various physical activities. Several examples are provided to highlight the capabilities and potential applications of the proposed protocol. This includes preliminary results on the role of body weight on the stresses and strains induced in the knee articular cartilages and meniscus during single-leg stance and calculations of the induced stresses and ligament forces during the gait cycle.     

The influence of patellofemoral joint contact geometry on the modeling of three dimensional patellofemoral joint forces

The purpose of this study was to determine the influence of patellofemoral joint contact geometry on the modeling of three-dimensional patellofemoral joint forces. To achieve this goal, patellofemoral joint reaction forces (PFJRFs) that were measured from an in-vitro cadaveric set-up were compared to PFJRFs estimated from a computer model that did not consider patellofemoral joint contact geometry. Ten cadaver knees were used in this study. Each was mounted on a custom jig that was fixed to an Instron frame. Quadriceps muscle loads were accomplished using a pulley system and weights. The force in the patellar ligament was obtained using a buckle transducer. To quantify the magnitude and direction of the PFJRF, a six-axis load cell was incorporated into the femoral fixation system so that a rigid body assumption could be made. PFJRF data were obtained at 0 degrees , 20 degrees , 40 degrees and 60 degrees of knee flexion. Following in vitro testing, SIMM modeling software was used to develop computational models based on the three-dimensional coordinates (Microscribe digitizer) of individual muscle and patellar ligament force vectors obtained from the cadaver knees. The overall magnitude of the PFJRF estimated from the computer generated models closely matched the direct measurements from the in vitro set-up (Pearson's correlation coefficient, R(2)=0.91, p<0.001). Although the computational model accurately estimated the posteriorly directed forces acting on the joint, some discrepancies were noted in the forces acting in the superior and lateral directions. These differences however, were relatively small when expressed as a total of the overall PFJRF magnitude.