An MRI-compatible foot-loading device for assessment of internal tissue deformation

It is well known that mechanical forces acting within the soft tissues of the foot can contribute to the formation of neuropathic ulcers in people with diabetes. Presently, only surface measurements of plantar pressure are used clinically to estimate risk status due to mechanical loading. It is currently not known how surface measurements relate to the three-dimensional (3-D) internal stress/strain state of the foot. This article describes the development of a foot-loading device that allows for the direct observation of the internal deformation of foot tissues under known forces. Ground reaction forces and plantar pressure distributions during normal walking were measured in ten healthy young adults. One instant in the gait cycle, when pressure under the metatarsal heads reached a peak, was extracted for simulation in an MR imager. T1-weighted 3-D gradient echo MRI sets were collected as the simulated walking ground reaction force was incrementally applied to the foot by the novel foot-loading device. The sub-metatarsal head soft-tissue thickness decreased rapidly at first and then reached a plateau. Peak plantar pressure measurements collected within the loading device (161+/-75kPa) were lower in magnitude and less focal than pressures measured during walking (492+/-91kPa). This finding implies that although the device successfully applied full peak walking ground reaction forces to the foot, they were not distributed in the same manner as during walking. Although not representative of gait, the data collected from this in vivo mechanical test are suitable for determination of foot tissue material properties or, when combined with finite element modeling, to examine the relationship between surface loading and internal stress.     

A 3D lower limb musculoskeletal model for simultaneous estimation of musculo-tendon,joint contact,ligament and bone forces during gait

Musculo-tendon forces and joint reaction forces are typically estimated using a two-step method, computing first the musculo-tendon forces by a static optimization procedure and then deducing the joint reaction forces from the force equilibrium. However, this method does not allow studying the interactions between musculo-tendon forces and joint reaction forces in establishing this equilibrium and the joint reaction forces are usually overestimated. This study introduces a new 3D lower limb musculoskeletal model based on a one-step static optimization procedure allowing simultaneous musculo-tendon, joint contact, ligament and bone forces estimation during gait. It is postulated that this approach, by giving access to the forces transmitted by these musculoskeletal structures at hip, tibiofemoral, patellofemoral and ankle joints, modeled using anatomically consistent kinematic models, should ease the validation of the model using joint contact forces measured with instrumented prostheses. A blinded validation based on four datasets was made under two different minimization conditions (i.e., C1 – only musculo-tendon forces are minimized, and C2 – musculo-tendon, joint contact, ligament and bone forces are minimized while focusing more specifically on tibiofemoral joint contacts). The results show that the model is able to estimate in most cases the correct timing of musculo-tendon forces during normal gait (i.e., the mean coefficient of active/inactive state concordance between estimated musculo-tendon force and measured EMG envelopes was C1: 65.87% and C2: 60.46%). The results also showed that the model is potentially able to well estimate joint contact, ligament and bone forces and more specifically medial (i.e., the mean RMSE between estimated joint contact force and in vivo measurement was C1: 1.14BW and C2: 0.39BW) and lateral (i.e., C1: 0.65BW and C2: 0.28BW) tibiofemoral contact forces during normal gait. However, the results remain highly influenced by the optimization weights that can bring to somewhat aphysiological musculo-tendon forces.     

Study of micromotion in modular acetabular components during gait and subluxation: a finite element investigation

Polyethylene wear after total hip arthroplasty may occur as a result of normal gait and as a result of subluxation and relocation with impact. Relocation of a subluxed hip may impart a moment to the cup creating sliding as well as compression at the cup liner interface. The purpose of the current study is to quantify, by a validated finite element model, the forces generated in a hip arthroplasty as a result of subluxation relocation and compare them to the forces generated during normal gait. The micromotion between the liner and acetabular shell was quantified by computing the sliding track and the deformation at several points of the interface. A finite element analysis of polyethylene liner stress and liner/cup micromotion in total hip arthroplasty was performed under two dynamic profiles. The first profile was a gait loading profile simulating the force vectors developed in the hip arthroplasty during normal gait. The second profile is generated during subluxation and subsequent relocation of the femoral head. The forces generated by subluxation relocation of a total hip arthroplasty can exceed those forces generated during normal gait. The induced micromotion at the cup polyethylene interface as a result of subluxation can exceed micromotion as a result of the normal gait cycle. This may play a significant role in the generation of backsided wear. Minimizing joint subluxation by restoring balance to the hip joint after arthroplasty should be explored as a strategy to minimize backsided wear.     

A novel gait platform to measure isolated plantar metatarsal forces during walking

A new gait platform described in this report allows an isolated measurement of the vertical and shear forces under an individual metatarsal head during barefoot walking. The apparatus incorporated a customized tactile force sensor and a high-speed camera system, which enabled easy identification of a single anatomical landmark at the forefoot’s plantar surface that is in contact with the sensor throughout stance. After calibration, the measured peak forces under the 2nd MTH showed variability of 3.7%, 9.2%, and 8.9% in vertical, anterior–posterior, and medial–lateral directions, respectively. The device therefore provides information about the magnitude and timing of such local metatarsal forces, and has been shown to be of significant research and clinical interest. Its ability to achieve this with a high degree of accuracy ensures its potential as a valuable research tool.     

PCA-based SVM for automatic recognition of gait patterns

In this technical note, we investigate a combination PCA with SVM to classify gait pattern based on kinetic data. The gait data of 30 young and 30 elderly participants were recorded using a strain gauge force platform during normal walking. The gait features were first extracted from the recorded vertical directional foot- ground reaction forces curve using PCA, and then these extracted features were adopted to develop the SVM gait classifier. The test results indicated that the performance of PCA-based SVM was on average 90% to recognize young- elderly gait patterns, resulting in a markedly improved performance over an artificial neural network-based classifier. The classification ability of the SVM with polynomial and radial basis function kernels was superior to that of the SVM with linear kernel. These results suggest that the proposed technique could provide an effective tool for gait classification in future clinical applications.     

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.     

Model of loadings acting on the femoral bone during gait

An evaluation of the model of loadings acting on the femoral bone during the whole gait cycle was the main aim of the paper. A computer simulation of the musculoskeletal system based on the gait data collected during gait was used to determine the muscle forces as well as the hip joint reaction. Kinematic parameters as well as the ground reaction force for ninety-nine healthy persons of both sexes (18–36 years old) who had no history of musculoskeletal disease were registered during normal gait with preferred speed and used as inputs for musculoskeletal modelling and numerical simulation with the use of the AnyBody software. Time waveforms of the values of force generated by 21 muscles having attachments on the femoral bone as well as the hip joint reaction force were obtained. Directions of particular forces were presented using a femoral coordinate system. Attachment points for all muscle forces were obtained on the basis of the unscaled standard model with the length of the femur equal to 0.41 m. The presented model of loadings acting on the femoral bone element can be useful for the biomechanical analysis of bone development and remodelling as well as for the optimisation of implant or bone stabilizer design and pre-clinical testing.     

Comparative forefoot trabecular bone architecture in extant hominids

The appearance of a forefoot push-off mechanism in the hominin lineage has been difficult to identify, partially because researchers disagree over the use of the external skeletal morphology to differentiate metatarsophalangeal joint functional differences in extant great apes and humans. In this study, we approach the problem by quantifying properties of internal bone architecture that may reflect different loading patterns in metatarsophalangeal joints in humans and great apes. High-resolution x-ray computed tomography data were collected for first and second metatarsal heads of Homo sapiens (n = 26), Pan paniscus (n = 17), Pan troglodytes (n = 19), Gorilla gorilla (n = 16), and Pongo pygmaeus (n = 20). Trabecular bone fabric structure was analyzed in three regions of each metatarsal head. While bone volume fraction did not significantly differentiate human and great ape trabecular bone structure, human metatarsal heads generally show significantly more anisotropic trabecular bone architectures, especially in the dorsal regions compared to the corresponding areas of the great ape metatarsal heads. The differences in anisotropy between humans and great apes support the hypothesis that trabecular architecture in the dorsal regions of the human metatarsals are indicative of a forefoot habitually used for propulsion during gait. This study provides a potential route for predicting forefoot function and gait in fossil hominins from metatarsal head trabecular bone architecture.     

An efficient probabilistic methodology for incorporating uncertainty in body segment parameters and anatomical landmarks in joint loadings estimated from inverse dynamics

Inverse dynamics is a standard approach for estimating joint loadings in the lower extremity from kinematic and ground reaction data for use in clinical and research gait studies. Variability in estimating body segment parameters and uncertainty in defining anatomical landmarks have the potential to impact predicted joint loading. This study demonstrates the application of efficient probabilistic methods to quantify the effect of uncertainty in these parameters and landmarks on joint loading in an inverse-dynamics model, and identifies the relative importance of the parameters and landmarks to the predicted joint loading. The inverse-dynamics analysis used a benchmark data set of lower-extremity kinematics and ground reaction data during the stance phase of gait to predict the three-dimensional intersegmental forces and moments. The probabilistic analysis predicted the 1-99 percentile ranges of intersegmental forces and moments at the hip, knee, and ankle. Variabilities, in forces and moments of up to 56% and 156% of the mean values were predicted based on coefficients of variation less than 0.20 for the body segment parameters and standard deviations of 2 mm for the anatomical landmarks. Sensitivity factors identified the important parameters for the specific joint and component directions. Anatomical landmarks affected moments to a larger extent than body segment parameters. Additionally, for forces, anatomical landmarks had a larger effect than body segment parameters, with the exception of segment masses, which were important to the proximal-distal joint forces. The probabilistic modeling approach predicted the range of possible joint loading, which has implications in gait studies, clinical assessments, and implant design evaluations.     

Direct comparison of measured and calculated total knee replacement force envelopes during walking in the presence of normal and abnormal gait patterns

Knee joint forces measured from instrumented implants provide important information for testing the validity of computational models that predict knee joint forces. The purpose of this study was to validate a parametric numerical model for predicting knee joint contact forces against measurements from four subjects with instrumented TKRs during the stance phase of gait. Model sensitivity to abnormal gait patterns was also investigated. The results demonstrated good agreement for three subjects with relatively normal gait patterns, where the difference between the mean measured and calculated forces ranged from 0.05 to 0.45 body weights, and the envelopes of measured and calculated forces (from three walking trials) overlapped. The fourth subject, who had a "quadriceps avoidance" external moment pattern, initially had little overlap between the measured and calculated force envelopes. When additional constraints were added, tailored to the subject's gait pattern, the model predictions improved to complete force envelope overlap. Coefficient of multiple determination analysis indicated that the shape of the measured and calculated force waveforms were similar for all subjects (adjusted coefficient of multiple correlation values between 0.88 and 0.92). The parametric model was accurate in predicting both the magnitude and waveform of the contact force, and the accuracy of model predictions was affected by deviations from normal gait patterns. Equally important, the envelope of forces generated by the range of solutions substantially overlapped with the corresponding measured envelope from multiple gait trials for a given subject, suggesting that the variable strategic processes of in vivo force generation are covered by the solution range of this parametric model.     

Hip contact forces and gait patterns from routine activities.

In vivo loads acting at the hip joint have so far only been measured in few patients and without detailed documentation of gait data. Such information is required to test and improve wear, strength and fixation stability of hip implants. Measurements of hip contact forces with instrumented implants and synchronous analyses of gait patterns and ground reaction forces were performed in four patients during the most frequent activities of daily living. From the individual data sets an average was calculated. The paper focuses on the loading of the femoral implant component but complete data are additionally stored on an associated compact disc. It contains complete gait and hip contact force data as well as calculated muscle activities during walking and stair climbing and the frequencies of daily activities observed in hip patients. The mechanical loading and function of the hip joint and proximal femur is thereby completely documented. The average patient loaded his hip joint with 238% BW (percent of body weight) when walking at about 4 km/h and with slightly less when standing on one leg. This is below the levels previously reported for two other patients (Bergmann et al., Clinical Biomechanics 26 (1993) 969-990). When climbing upstairs the joint contact force is 251% BW which is less than 260% BW when going downstairs. Inwards torsion of the implant is probably critical for the stem fixation. On average it is 23% larger when going upstairs than during normal level walking. The inter- and intra-individual variations during stair climbing are large and the highest torque values are 83% larger than during normal walking. Because the hip joint loading during all other common activities of most hip patients are comparably small (except during stumbling), implants should mainly be tested with loading conditions that mimic walking and stair climbing.     

A biomechanical model for the analysis of the cervical spine in static postures.

To gain a better understanding of the forces working on the cervical spine, a spatial biomechanical computer model was developed. The first part of our research was concerned with the development of a kinematic model to establish the axes of rotation and the mutual position of the head and vertebrae with regard to flexion, extension, lateroflexion and torsion. The next step was the introduction of lines of action of muscle forces and an external load, created by gravity and accelerations in different directions, working on the centre of gravity of the head and possibly a helmet. Although the results of our calculations should be interpreted cautiously in the present stage of our research, some conclusions can be drawn with respect to different head positions. During flexion muscle forces and joint reaction forces increase, except the force between the odontoid and the ligamentum transversum atlantis. This force shows a minimum during moderate flexion. The joint reaction forces on the levels C0-C1, C1-C2, and C7-T1 reach minimum values during extension, each in different stages of extension. Axial rotation less than 35 degrees does not need great muscle forces, axial rotation further than 35 degrees causes muscle forces and joint reaction forces to increase fast. While performing, lateral flexion muscle forces and joint reaction forces must increase rapidly to balance the head. We obtained some indications that the order of magnitude of the calculated forces is correct.     

Pattern of anterior cruciate ligament force in normal walking

The goal of this study was to calculate and explain the pattern of anterior cruciate ligament (ACL) loading during normal level walking. Knee-ligament forces were obtained by a two-step procedure. First, a three-dimensional (3D) model of the whole body was used together with dynamic optimization theory to calculate body-segmental motions, ground reaction forces, and leg-muscle forces for one cycle of gait. Joint angles, ground reaction forces, and muscle forces obtained from the gait simulation were then input into a musculoskeletal model of the lower limb that incorporated a 3D model of the knee. The relative positions of the femur, tibia, and patella and the forces induced in the knee ligaments were found by solving a static equilibrium problem at each instant during the simulated gait cycle. The model simulation predicted that the ACL bears load throughout stance. Peak force in the ACL (303 N) occurred at the beginning of single-leg stance (i.e., contralateral toe off). The pattern of ACL force was explained by the shear forces acting at the knee. The balance of muscle forces, ground reaction forces, and joint contact forces applied to the leg determined the magnitude and direction of the total shear force acting at the knee. The ACL was loaded whenever the total shear force pointed anteriorly. In early stance, the anterior shear force from the patellar tendon dominated the total shear force applied to the leg, and so maximum force was transmitted to the ACL at this time. ACL force was small in late stance because the anterior shear forces supplied by the patellar tendon, gastrocnemius, and tibiofemoral contact were nearly balanced by the posterior component of the ground reaction.     

An upper extremity inverse dynamics model for pediatric Lofstrand crutch-assisted gait

The objective of this study was to develop an instrumented Lofstrand crutch system, which quantifies three-dimensional (3-D) upper extremity (UE) kinematics and kinetics using an inverse dynamics model. The model describes the dynamics of the shoulders, elbows, wrists, and crutches and is compliant with the International Society of Biomechanics (ISB) recommended standards. A custom designed Lofstrand crutch system with four, six-degree-of-freedom force transducers was implemented with the inverse dynamics model to obtain triaxial UE joint reaction forces and moments. The crutch system was validated statically and dynamically for accuracy of computing joint reaction forces and moments during gait. The root mean square (RMS) error of the system ranged from 0.84 to 5.20%. The system was demonstrated in children with diplegic cerebral palsy (CP), incomplete spinal cord injury (SCI), and type I osteogenesis imperfecta (OI). The greatest joint reaction forces were observed in the posterior direction of the wrist, while shoulder flexion moments were the greatest joint reaction moments. The subject with CP showed the highest forces and the subject with SCI demonstrated the highest moments. Dynamic quantification may help to elucidate UE joint demands in regard to pain and pathology in long-term assistive device users.     

Quantitative assessment of gait determinants during single stance via a three-dimensional model--Part 1. Normal gait

In this two-part paper, a variety of three-dimensional, dynamical models are constructed for simulating the single support phases of normal and pathological human gait. A major objective of this work is to quantify the influence of individual gait determinants on the ground reaction forces generated during normal, level walking. To this end, Part 1 presents a three-dimensional, seven degree-of-freedom model incorporating five of the six fundamental determinants of gait. On the basis of crude muscle-force and/or joint-moment trajectories, body-segmental motions and ground reaction forces are synthesized open loop. Through a quantitative comparison with experimental gait data, the model's predictions are evaluated. Our simulation results suggest that pelvic list is not as dominant a dynamical determinant as either stance knee flexion-extension or foot and knee interaction. Transverse pelvic rotation, however, makes an important contribution by limiting the magnitude of the horizontal ground reaction prior to opposite heel-strike.     

Optimization-based prediction of asymmetric human gait

An optimization-based formulation and solution method are presented to predict asymmetric human gait for a large-scale skeletal model. Predictive dynamics approach is used in which both the joint angles and joint torques are treated as unknowns in the equations of motion. For the optimization formulation, the joint angle profiles are treated as the primary unknowns, and velocities and accelerations are calculated using them. In numerical implementation, the joint angle profiles are discretized using the B-spline interpolation. An algorithm is presented to inversely calculate the joint torques and the ground reaction forces. The sum of the joint-torques squared, called the dynamic effort, is minimized as the human performance measure. Constraints are imposed on the joint strengths (torques) and joint ranges of motion along with other physical constraints. The formulation is validated by simulating a symmetric gait and comparing the results with the experimental data. Then asymmetric gait motion is simulated, where the left and right step lengths are different. The kinematics and kinetics results from the simulation are presented and discussed. Predicted ground reaction forces are explained by using the inverted pendulum model. Predicted kinematics and kinetics have trends that are similar to those reported in the literature. Potential practical applications of the formulation and the solution approach are discussed.     

Static and dynamic optimization solutions for gait are practically equivalent

The proposition that dynamic optimization provides better estimates of muscle forces during gait than static optimization is examined by comparing a dynamic solution with two static solutions. A 23-degree-of-freedom musculoskeletal model actuated by 54 Hill-type musculotendon units was used to simulate one cycle of normal gait. The dynamic problem was to find the muscle excitations which minimized metabolic energy per unit distance traveled, and which produced a repeatable gait cycle. In the dynamic problem, activation dynamics was described by a first-order differential equation. The joint moments predicted by the dynamic solution were used as input to the static problems. In each static problem, the problem was to find the muscle activations which minimized the sum of muscle activations squared, and which generated the joint moments input from the dynamic solution. In the first static problem, muscles were treated as ideal force generators; in the second, they were constrained by their force-length-velocity properties; and in both, activation dynamics was neglected. In terms of predicted muscle forces and joint contact forces, the dynamic and static solutions were remarkably similar. Also, activation dynamics and the force-length-velocity properties of muscle had little influence on the static solutions. Thus, for normal gait, if one can accurately solve the inverse dynamics problem and if one seeks only to estimate muscle forces, the use of dynamic optimization rather than static optimization is currently not justified. Scenarios in which the use of dynamic optimization is justified are suggested.     

Musculoskeletal model choice influences hip joint load estimations during gait

The prevalence of musculoskeletal modeling studies investigating hip contact forces and the number of models used to conduct such investigations has increased in recent years. However, the consistency between models remain unknown and differences in model predicted hip contact forces between studies are difficult to distinguish from natural inter-individual differences. The purpose of this study was therefore to evaluate differences in hip joint contact forces during gait between four OpenSim models. These models included the generic models gait2392 and the Arnold Lower Limb Model, as well as the hip specific models hip2372 and London Lower Limb Model. Data from four individuals who have had a total hip replacement with instrumented hip implants performing slow, normal, and fast walking trials were taken from the HIP98 database to evaluate the various models effectiveness at estimating hip loads. Muscle forces were estimated using static optimization and hip contact forces were calculated using the JointReaction analysis in OpenSim. Results indicated that, for gait, the hip specific London Lower Limb Model consistently predicted peak push-off hip joint contact forces with lower magnitude and timing errors compared to the other models. Likewise, root mean square error values were lowest and correlation coefficients were highest for the London Lower Limb Model. These results suggest that the London Lower Limb Model is the most appropriate model for investigations focused on hip joint loading.     

The effect of a 12-week combined exercise intervention program on physical performance and gait kinematics in community-dwelling elderly women

This study aimed to determine if combined exercise intervention improves physical performance and gait joint-kinematics including the joint angle and dynamic range of motion (ROM) related to the risk of falling in community-dwelling elderly women. A 12-week combined exercise intervention program with extra emphasis on balance, muscle strength, and walking ability was designed to improve physical performance and gait. Twenty participants attended approximately two-hour exercise sessions twice weekly for 12 weeks. Participants underwent a physical performance battery, including static balance, sit and reach, whole body reaction time, 10 m obstacle walk, 10 m maximal walk, 30-second chair stand, to determine a physical performance score, and received quantitative gait kinematics measurements at baseline and in 12 weeks. Significant lower extremity strength improvement 13.5% (p<.001) was observed, which was accompanied by significant decreases in time of the 10 m obstacle walk (p<.05) and whole body reaction time (p<.001) in this study. However, no significant differences were seen for static balance and flexibility from baseline. For gait kinematics, in the mid-swing phase, knee and hip joint angle changed toward flexion (p<.01, p<.05, respectively). Ankle dynamic ROM significantly increased (p<.05) following exercise intervention. The plantar flexion angle of the ankle in the toe-off phase was increased significantly (p<.01). However, other gait parameters were not significantly different from baseline. These findings from the present investigation provide evidence of significant improvements in physical performance related to the risk factors of falling and safe gait strategy with a combined exercise intervention program in community-dwelling elderly women. The results suggest this exercise intervention could be an effective approach to ameliorate the risk factors for falls and to promote safer locomotion in elderly community-dwelling women.