Validity of Inertial Measurement Units to Measure Lower-Limb Kinematics and Pelvic Orientation at Submaximal and Maximal Effort Running Speeds.

Inertial measurement units (IMUs) have been validated for measuring sagittal plane lower-limb kinematics during moderate-speed running, but their accuracy at maximal speeds remains less understood. This study aimed to assess IMU measurement accuracy during high-speed running and maximal effort sprinting on a curved non-motorized treadmill using discrete (Bland-Altman analysis) and continuous (root mean square error [RMSE], normalised RMSE, Pearson correlation, and statistical parametric mapping analysis [SPM]) metrics. The hip, knee, and ankle flexions and the pelvic orientation (tilt, obliquity, and rotation) were captured concurrently from both IMU and optical motion capture systems, as 20 participants ran steadily at 70%, 80%, 90%, and 100% of their maximal effort sprinting speed (5.36 ± 0.55, 6.02 ± 0.60, 6.66 ± 0.71, and 7.09 ± 0.73 m/s, respectively). Bland-Altman analysis indicated a systematic bias within ±1° for the peak pelvic tilt, rotation, and lower-limb kinematics and -3.3° to -4.1° for the pelvic obliquity. The SPM analysis demonstrated a good agreement in the hip and knee flexion angles for most phases of the stride cycle, albeit with significant differences noted around the ipsilateral toe-off. The RMSE ranged from 4.3° (pelvic obliquity at 70% speed) to 7.8° (hip flexion at 100% speed). Correlation coefficients ranged from 0.44 (pelvic tilt at 90%) to 0.99 (hip and knee flexions at all speeds). Running speed minimally but significantly affected the RMSE for the hip and ankle flexions. The present IMU system is effective for measuring lower-limb kinematics during sprinting, but the pelvic orientation estimation was less accurate.

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a deep neural network (DNN)-based drug-target interaction (DTI) model and drug design specifications is proposed to design a potential multiple-molecule drug for the medical treatment of OSCC before clinical trials. First, we use big database mining to construct the candidate genome-wide genetic and epigenetic network (GWGEN) including a protein-protein interaction network (PPIN) and a gene regulatory network (GRN) for OSCC and non-OSCC. In the next step, real GWGENs are identified for OSCC and non-OSCC by system identification and system order detection methods based on the OSCC and non-OSCC microarray data, respectively. Then, the principal network projection (PNP) method was used to extract core GWGENs of OSCC and non-OSCC from real GWGENs of OSCC and non-OSCC, respectively. Afterward, core signaling pathways were constructed through the annotation of KEGG pathways, and then the carcinogenic mechanism of OSCC was investigated by comparing the core signal pathways and their downstream abnormal cellular functions of OSCC and non-OSCC. Consequently, HES1, TCF, NF-κB and SP1 are identified as significant biomarkers of OSCC. In order to discover multiple molecular drugs for these significant biomarkers (drug targets) of the carcinogenic mechanism of OSCC, we trained a DNN-based drug-target interaction (DTI) model by DTI databases to predict candidate drugs for these significant biomarkers. Finally, drug design specifications such as adequate drug regulation ability, low toxicity and high sensitivity are employed to filter out the appropriate molecular drugs metformin, gefitinib and gallic-acid to combine as a potential multiple-molecule drug for the therapeutic treatment of OSCC.

How muscles maximize performance in accelerated sprinting.

We sought to provide a more comprehensive understanding of how the individual leg muscles act synergistically to generate a ground force impulse and maximize the change in forward momentum of the body during accelerated sprinting. We combined musculoskeletal modelling with gait data to simulate the majority of the acceleration phase (19 foot contacts) of a maximal sprint over ground. Individual muscle contributions to the ground force impulse were found by evaluating each muscle's contribution to the vertical and fore-aft components of the ground force (termed "supporter" and "accelerator/brake," respectively). The ankle plantarflexors played a major role in achieving maximal-effort accelerated sprinting. Soleus acted primarily as a supporter by generating a large fraction of the upward impulse at each step whereas gastrocnemius contributed appreciably to the propulsive and upward impulses and functioned as both accelerator and supporter. The primary role of the vasti was to deliver an upward impulse to the body (supporter), but these muscles also acted as a brake by retarding forward momentum. The hamstrings and gluteus medius functioned primarily as accelerators. Gluteus maximus was neither an accelerator nor supporter as it functioned mainly to decelerate the swinging leg in preparation for foot contact at the next step. Fundamental knowledge of lower-limb muscle function during maximum acceleration sprinting is of interest to coaches endeavoring to optimize sprint performance in elite athletes as well as sports medicine clinicians aiming to improve injury prevention and rehabilitation practices.

Direct Validation of Model-Predicted Muscle Forces in the Cat Hindlimb During Locomotion.

Various methods are available for simulating the movement patterns of musculoskeletal systems and determining individual muscle forces, but the results obtained from these methods have not been rigorously validated against experiment. The aim of this study was to compare model predictions of muscle force derived for a cat hindlimb during locomotion against direct measurements of muscle force obtained in vivo. The cat hindlimb was represented as a 5-segment, 13-degrees-of-freedom (DOF), articulated linkage actuated by 25 Hill-type muscle-tendon units (MTUs). Individual muscle forces were determined by combining gait data with two widely used computational methods-static optimization and computed muscle control (CMC)-available in opensim, an open-source musculoskeletal modeling and simulation environment. The forces developed by the soleus, medial gastrocnemius (MG), and tibialis anterior muscles during free locomotion were measured using buckle transducers attached to the tendons. Muscle electromyographic activity and MTU length changes were also measured and compared against the corresponding data predicted by the model. Model-predicted muscle forces, activation levels, and MTU length changes were consistent with the corresponding quantities obtained from experiment. The calculated values of muscle force obtained from static optimization agreed more closely with experiment than those derived from CMC.

Validation of a new simple scale to measure symptoms in heart failure from traditional Chinese medicine view: a cross-sectional questionnaire study.

BACKGROUND: Current clinical practices used to functionally classify heart failure (HF) are time-consuming, expensive, or require complex calculations. This study aimed to design an inquiry list from the perspective of traditional Chinese medicine (TCM) that could be used in routine clinical practice to resolve these problems. METHODS: The severity of documented HF in 115 patients was classified according to their performance in maximal exercise tests into New York Heart Association (NYHA) functional classification (FC) II or NYHA FC III. Concomitantly, the patients were assessed using the new TCM inquiry list and two validated quality of life questionnaires, namely, the Short Form 36 (SF-36) generic scale and the Minnesota Living with Heart Failure Questionnaire (MLHFQ). Factor analysis was applied to extract the core factors from the responses to the items in TCM inquiry list; logistic regression analysis was then used to predict the severity of HF according to the extracted factors. RESULTS: The TCM inquiry list showed moderate levels of correlation with the physical and emotional components of the SF-36 and the MLHFQ, and predicted the functional class of HF patients reliably using logistic regression analysis, with a correct prediction rate with 64.3 %. Factor analysis of the TCM inquiry list extracted five core factors, namely, Qi Depression, Heart Qi Vacuity and Blood Stasis, Heart Blood Vacuity, Dual Qi-Blood Vacuity, and Yang Vacuity, from the list, which aligned with the perspective of TCM as it relates to the pattern of HF. The correct prediction rate rose to 70.4 % when Dual Qi-Blood Vacuity was combined with the MLHFQ. The excessive false-negative rate is a problem associated with the TCM inquiry list. CONCLUSIONS: The TCM inquiry list is a simple scale and similar to patient-reported subjective measures of quality of life in HF, and may help to classify patients into NYHA FC II or NYHA FC III. Factor 4 addresses dizziness, dizzy vision and general weakness, which are critical parameters that distinguish between NYHA FC II and NYHA FC III. Incorporating these three items into the management of HF may help to classify patients from a functional perspective.

Tendon elastic strain energy in the human ankle plantar-flexors and its role with increased running speed.

The human ankle plantar-flexors, the soleus and gastrocnemius, utilize tendon elastic strain energy to reduce muscle fiber work and optimize contractile conditions during running. However, studies to date have considered only slow to moderate running speeds up to 5 m s(-1). Little is known about how the human ankle plantar-flexors utilize tendon elastic strain energy as running speed is advanced towards maximum sprinting. We used data obtained from gait experiments in conjunction with musculoskeletal modeling and optimization techniques to calculate muscle-tendon unit (MTU) work, tendon elastic strain energy and muscle fiber work for the ankle plantar-flexors as participants ran at five discrete steady-state speeds ranging from jogging (~2 m s(-1)) to sprinting (≥8 m s(-1)). As running speed progressed from jogging to sprinting, the contribution of tendon elastic strain energy to the positive work generated by the MTU increased from 53% to 74% for the soleus and from 62% to 75% for the gastrocnemius. This increase was facilitated by greater muscle activation and the relatively isometric behavior of the soleus and gastrocnemius muscle fibers. Both of these characteristics enhanced tendon stretch and recoil, which contributed to the bulk of the change in MTU length. Our results suggest that as steady-state running speed is advanced towards maximum sprinting, the human ankle plantar-flexors continue to prioritize the storage and recovery of tendon elastic strain energy over muscle fiber work.

Patellofemoral joint loading during stair ambulation in people with patellofemoral osteoarthritis.

OBJECTIVE: To determine whether people with patellofemoral (PF) joint osteoarthritis (OA) ascend and descend stairs with different PF joint loading, knee joint moments, lower limb kinematics, and muscle forces compared to healthy people. METHODS: We recruited 17 participants with isolated PF joint OA, 13 participants with concurrent PF joint OA and tibiofemoral (TF) joint OA, and 21 age-matched controls. Joint kinematics and ground reaction forces were measured while participants ascended and descended stairs at a self-selected speed. Musculoskeletal computer modeling was used to determine lower limb muscle forces and the PF joint reaction force, and these parameters were compared between groups by analysis of variance. RESULTS: Compared to their healthy counterparts, participants with isolated PF joint OA and participants with concurrent PF and TF joint OA ascended and descended stairs with lower knee extension moments, lower quadriceps muscle forces, lower PF joint reaction forces, and increased anterior pelvic tilt. Participants with OA also ascended stairs with increased hip flexion angles and descended stairs with smaller knee flexion angles and smaller hip abductor muscle forces. No differences were evident between the two groups with OA. CONCLUSION: Compared to their healthy counterparts, people with PF joint OA (with or without concurrent TF joint OA) exhibit lower PF joint reaction forces during stair ascent and descent, in conjunction with lower knee extension moments and lower quadriceps muscle forces.

In vitro efficacies and resistance profiles of rifampin-based combination regimens for biofilm-embedded methicillin-resistant Staphylococcus aureus.

To compare the in vitro antibacterial efficacies and resistance profiles of rifampin-based combinations against methicillin-resistant Staphylococcus aureus (MRSA) in a biofilm model, the antibacterial activities of vancomycin, teicoplanin, daptomycin, minocycline, linezolid, fusidic acid, fosfomycin, and tigecycline alone or in combination with rifampin against biofilm-embedded MRSA were measured. The rifampin-resistant mutation frequencies were evaluated. Of the rifampin-based combinations, rifampin enhances the antibacterial activities of and even synergizes with fusidic acid, tigecycline, and, to a lesser extent, linezolid, fosfomycin, and minocycline against biofilm-embedded MRSA. Such combinations with weaker rifampin resistance induction activities may provide a therapeutic advantage in MRSA biofilm-related infections.

Influence of muscle loading on early-stage bone fracture healing.

Designing weight-bearing exercises for patients with lower-limb bone fractures is challenging and requires a systematic approach that accounts for patient-specific loading conditions. However, 'trial-and-error' approaches are commonplace in clinical settings due to the lack of a fundamental understanding of the effect of weight-bearing exercises on the bone healing process. Whilst computational modelling has the potential to assist clinicians in designing effective patient-specific weight-bearing exercises, current models do not explicitly account for the effects of muscle loading, which could play an important role in mediating the mechanical microenvironment of a fracture site. We combined a fracture healing model involving a tibial fracture stabilised with a locking compression plate (LCP) with a detailed musculoskeletal model of the lower limb to determine interfragmentary strains in the vicinity of the fracture site during both full weight-bearing (100% body weight) and partial weight-bearing (50% body weight) standing. We found that muscle loading significantly altered model predictions of interfragmentary strains. For a fractured bone with a standard LCP configuration (bone-plate distance = 2 mm, working length = 30 mm) subject to full weight-bearing, the predicted strains at the near and far cortices were 23% and 11% higher when muscle loading was included compared to the case when muscle loading was omitted. The knee and ankle muscles accounted for 38% of the contact force exerted at the knee joint during quiet standing and contributed significantly to the strains calculated at the fracture site. Thus, models of bone fracture healing ought to account explicitly for the effects of muscle loading. Furthermore, the study indicated that LCP configuration parameters play a crucial role in influencing the fracture site microenvironment. The results highlighted the dominance of working length over bone-plate distance in controlling the flexibility of fracture sites stabilised with LCP devices.

Comparison of different methods for estimating muscle forces in human movement.

The aim of this study was to compare muscle-force estimates derived for human locomotion using three different methods commonly reported in the literature: static optimisation (SO), computed muscle control (CMC) and neuromusculoskeletal tracking (NMT). In contrast with SO, CMC and NMT calculate muscle forces dynamically by including muscle activation dynamics. Furthermore, NMT utilises a time-dependent performance criterion, wherein a single optimisation problem is solved over the entire time interval of the task. Each of these methods was used in conjunction with musculoskeletal modelling and experimental gait data to determine lower-limb muscle forces for self-selected speeds of walking and running. Correlation analyses were performed for each muscle to quantify differences between the various muscle-force solutions. The patterns of muscle loading predicted by the three methods were similar for both walking and running. The correlation coefficient between any two sets of muscle-force solutions ranged from 0.46 to 0.99 (p < 0.001 for all muscles). These results suggest that the robustness and efficiency of static optimisation make it the most attractive method for estimating muscle forces in human locomotion.

Predictive Simulations of Human Sprinting: Effects of Muscle-Tendon Properties on Sprint Performance.

PURPOSE: We combined a full-body musculoskeletal model with dynamic optimization theory to predict the biomechanics of maximum-speed sprinting and evaluate the effects of changes in muscle-tendon properties on sprint performance. METHODS: The body was modeled as a three-dimensional skeleton actuated by 86 muscle-tendon units. A simulation of jogging was used as an initial guess to generate a predictive dynamic optimization solution for maximum-speed sprinting. Nominal values of lower-limb muscle strength, muscle fascicle length, muscle intrinsic maximum shortening velocity (fiber-type composition), and tendon compliance were then altered incrementally to study the relative influence of each property on sprint performance. RESULTS: Model-predicted patterns of full-body motion, ground forces, and muscle activations were in general agreement with experimental data recorded for maximum-effort sprinting. Maximum sprinting speed was 1.3 times more sensitive to a change in muscle strength compared with the same change in muscle fascicle length, 2.0 times more sensitive to a change in muscle fascicle length compared with the same change in muscle intrinsic maximum shortening velocity, and 9.1 times more sensitive to a change in muscle intrinsic maximum shortening velocity compared with the same change in tendon compliance. A 10% increase in muscle strength increased maximum sprinting speed by 5.9%, whereas increasing muscle fascicle length, muscle intrinsic maximum shortening velocity, and tendon compliance by 10% increased maximum sprinting speed by 4.7%, 2.4%, and 0.3%, respectively. CONCLUSIONS: Sprint performance was most sensitive to changes in muscle strength and least affected by changes in tendon compliance. Sprint performance was also more heavily influenced by changes in muscle fascicle length than muscle intrinsic maximum shortening velocity. These results could inform training methods aimed at optimizing performance in elite sprinters.

Lower-limb muscle function in healthy young and older adults across a range of walking speeds.

BACKGROUND: Previous studies have compared the functional roles of the individual lower-limb muscles when healthy young and older adults walk at their self-selected speeds. No age-group differences were observed in ankle muscle forces and ankle muscle contributions to support and progression. However, older adults displayed higher gluteus maximus (hip extensor) muscle forces and greater contributions to support during early stance. There are no data that describe the functions of the individual lower-limb muscles in healthy older adults for walking at speeds other than the self-selected speed. RESEARCH QUESTION: How does walking speed affect the functional roles of the individual lower-limb muscles in healthy older adults? METHODS: Three-dimensional gait data were recorded for 10 healthy young and 10 healthy older adults walking at slow, normal, and fast speeds (0.7 m/s, 1.4 m/s, and 1.7 m/s, respectively). Both groups walked at the same speed at each condition. The experimental data were combined with a full-body musculoskeletal model to calculate and compare muscle forces and muscle contributions to the vertical, fore-aft, and mediolateral ground reaction forces (support, progression, and balance, respectively) in both groups. RESULTS: Lower-limb muscle function was similar in young and older adults when both groups walked at the same speed at each condition. The same five muscles - gluteus maximus, gluteus medius, vasti, gastrocnemius, and soleus - contributed most significantly to support, progression, and balance in both groups at all speeds. However, gluteus maximus generated greater support and braking forces during early stance and gastrocnemius contributed less to forward propulsion during late stance at all speeds in the older group. SIGNIFICANCE: These results provide further insight into the functional roles of the individual lower-limb muscles of older adults during walking and could inform the design of exercise programs aimed at improving support and balance in those at risk of falling.

A generic musculoskeletal model of the juvenile lower limb for biomechanical analyses of gait.

The aim of this study was to develop a generic musculoskeletal model of a healthy 10-year-old child and examine the effects of geometric scaling on the calculated values of lower-limb muscle forces during gait. Subject-specific musculoskeletal models of five healthy children were developed from in vivo MRI data, and these models were subsequently used to create a generic juvenile (GJ) model. Calculations of lower-limb muscle forces for normal walking obtained from two scaled-generic versions of the juvenile model (SGJ1 and SGJ2) were evaluated against corresponding results derived from an MRI-based model of one subject (SSJ1). The SGJ1 and SGJ2 models were created by scaling the GJ model using gait marker positions and joint centre locations derived from MRI imaging, respectively. Differences in the calculated values of peak isometric muscle forces and muscle moment arms between the scaled-generic models and MRI-based model were relatively small. Peak isometric muscle forces calculated for SGJ1 and SGJ2 were respectively 2.2% and 3.5% lower than those obtained for SSJ1. Model-predicted muscle forces for SGJ2 agreed more closely with calculations obtained from SSJ1 than corresponding results derived from SGJ1. These results suggest that accurate estimates of muscle forces during gait may be obtained by scaling generic juvenile models based on joint centre locations. The generic juvenile model developed in this study may be used as a template for creating subject-specific musculoskeletal models of normally-developing children in studies aimed at describing lower-limb muscle function during gait.

Load Distribution at the Patellofemoral Joint During Walking.

We combined computational modelling with experimental gait data to describe and explain load distribution across the medial and lateral facets of the patella during normal walking. The body was modelled as a 13-segment, 32-degree-of-freedom (DOF) skeleton actuated by 80 muscles. The knee was represented as a 3-body, 12-DOF mechanical system with deformable articular cartilage surfaces at the tibiofemoral (TF) and patellofemoral (PF) joints. Passive responses of the knee model to 100 N anterior-posterior drawer and 5 Nm axial torque tests were consistent with cadaver data reported in the literature. Trajectories of 6-DOF TF and PF joint motion and articular joint contact calculated for walking were also consistent with measurements obtained from biplane X-ray imaging. The force acting on the lateral patellar facet was considerably higher than that on the medial facet throughout the gait cycle. The vastus medialis, vastus lateralis and patellar tendon forces contributed substantially to the first peak in the PF contact force during stance whereas all three portions of the vasti and rectus femoris were responsible for the second peak during swing. A higher lateral patellar contact force was caused mainly by the laterally-directed shear force applied by the quadriceps muscles, especially the vastus lateralis, intermedius and rectus femoris. A better understanding of the contributions of the individual knee muscles to load distribution in the PF compartment may lead to improved surgical and physiotherapy methods to treat PF disorders.

In Vitro Synergy of Pongamia pinnata Extract in Combination with Antibiotics for Inhibiting and Killing Methicillin-Resistant Staphylococcus aureus.

AIMS: Currently, we face the serious problem of multiple drug-resistant pathogens. The development of new antimicrobial agents is very costly and time-consuming. Therefore, the use of medicinal plants as a source of alternative antibiotics or for enhancing antibiotic effectiveness is important. METHODS: The antibacterial effects of aqueous extracts of the seed coat of Pongamia pinnata (Linn.) Pierre in combination with several antibiotics against methicillin-resistant Staphylococcus aureus (MRSA) were tested by broth dilution, checkerboard, and time-kill methods. RESULTS: For the combinations of P. pinnata with ampicillin, meropenem, cefazolin, cefotaxime, cefpirome, and cefuroxime, 70% to 100% were synergistic, with a fractional inhibitory concentration (FIC) index of < 0.5. For the time-kill method with 0.5× minimum inhibitory concentration (MIC) of P. pinnata in combination with 8, 4, 2, and 1 µg mL-1 of the various antibiotics, almost all of the combinations showed synergistic effects, even with the lowest concentrations of P. pinnata, except for aztreonam. No antagonistic effect was observed for these combinations. CONCLUSIONS: Based on these findings, aqueous seed coat extracts of P. pinnata have good potential for the design of new antimicrobial agents.

Predictive Simulations of Neuromuscular Coordination and Joint-Contact Loading in Human Gait.

We implemented direct collocation on a full-body neuromusculoskeletal model to calculate muscle forces, ground reaction forces and knee contact loading simultaneously for one cycle of human gait. A data-tracking collocation problem was solved for walking at the normal speed to establish the practicality of incorporating a 3D model of articular contact and a model of foot-ground interaction explicitly in a dynamic optimization simulation. The data-tracking solution then was used as an initial guess to solve predictive collocation problems, where novel patterns of movement were generated for walking at slow and fast speeds, independent of experimental data. The data-tracking solutions accurately reproduced joint motion, ground forces and knee contact loads measured for two total knee arthroplasty patients walking at their preferred speeds. RMS errors in joint kinematics were < 2.0° for rotations and < 0.3 cm for translations while errors in the model-computed ground-reaction and knee-contact forces were < 0.07 BW and < 0.4 BW, respectively. The predictive solutions were also consistent with joint kinematics, ground forces, knee contact loads and muscle activation patterns measured for slow and fast walking. The results demonstrate the feasibility of performing computationally-efficient, predictive, dynamic optimization simulations of movement using full-body, muscle-actuated models with realistic representations of joint function.

Correction to: Predictive Simulations of Neuromuscular Coordination and Joint-Contact Loading in Human Gait.

In the "Materials and Methods" section, the link provided at the bottom of the second paragraph should be https://simtk.org/home/dcwithjtcontact/ .

Is Running Better than Walking for Reducing Hip Joint Loads?

PURPOSE: Knowledge of hip biomechanics during locomotion is necessary for designing optimal rehabilitation programs for hip-related conditions. The purpose of this study was to: 1) determine how lower-limb muscle contributions to the hip contact force (HCF) differed between walking and running; and 2) compare both absolute and per-unit-distance (PUD) loads at the hip during walking and running. METHODS: Kinematic and ground reaction force data were captured from eight healthy participants during overground walking and running at various steady-state speeds (walking: 1.50 ± 0.11 m·s and 1.98 ± 0.03 m·s; running: 2.15 ± 0.18 m·s and 3.47 ± 0.11 m·s). A three-dimensional musculoskeletal model was used to calculate the HCF as well as lower-limb muscular contributions to the HCF in each direction (posterior-anterior; inferior-superior; lateral-medial). The impulse of the resultant HCF was calculated as well as the PUD impulse (BW·s·m) and PUD force (BW·m). RESULTS: For both walking and running, HCF magnitude was greater during stance than swing and was largest in the inferior-superior direction and smallest in the posterior-anterior direction. Gluteus medius, iliopsoas, and gluteus maximus generated the largest contributions to the HCF during stance, whereas iliopsoas and hamstrings generated the largest contributions during swing. When comparing all locomotion conditions, the impulse of the resultant HCF was smallest for running at 2.15 m·s with an average magnitude of 2.14 ± 0.31 BW·s, whereas the PUD impulse and force were smallest for running at 3.47 m·s with average magnitudes of 0.95 ± 0.18 BW·s·m and 1.25 ± 0.24 BW·m, respectively. CONCLUSIONS: Hip PUD loads were lower for running at 3.47 m·s compared with all other locomotion conditions because of a greater distance travelled per stride (PUD impulse) or a shorter stride duration combined with a greater distance travelled per stride (PUD force).

Lower-limb muscle function during gait in varus mal-aligned osteoarthritis patients.

This study quantified the contributions by muscular, gravitational and inertial forces to the ground reaction force (GRF) and external knee adduction moment (EKAM) for knee osteoarthritis (OA) patients and controls walking at similar speeds. Gait data for 39 varus mal-aligned medial knee OA patients and 15 controls were input into musculoskeletal models to calculate the contributions of individual muscles and gravity to the fore-aft (progression), vertical (support), and mediolateral (balance) GRF, and the EKAM. The temporal patterns of contributions to GRF and EKAM were similar between the groups. Magnitude differences in GRF contributions were small but some reached significance. Peak GRF contributions were lower in patients except hamstrings in early-stance progression (p < 0.001) and gastrocnemius in late-stance progression (p < 0.001). Both EKAM peaks were higher in patients, due mainly to greater adduction contribution from gravity (p < 0.001) at the first peak, and lower abduction contributions from soleus (p < 0.001) and gastrocnemius (p < 0.001) at the second peak. Gluteus medius contributed most to EKAM in both groups, but was higher in patients during mid-stance only (p < 0.001). Differences in GRF contributions were attributed to altered quadriceps-hamstrings action as well as compensatory adaptation of the ankle plantarflexors to reduced gluteus medius action. The large effect of varus mal-alignment on the frontal-plane moment arms of the gravity, soleus, and gastrocnemius GRF contributions about the knee explained greater patient EKAM. Our results shed further light on how the EKAM contributes to altered knee-joint loads in OA and why some interventions may affect different portions of the EKAM waveform. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking.