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

Influence of Muscle-Tendon Wrapping on Calculations of Joint Reaction Forces in the Equine Distal Forelimb

The equine distal forelimb is a common location of injuries related to mechanical overload. In this study, a two-dimensional model of the musculoskeletal system of the region was developed and applied to kinematic and kinetic data from walking and trotting horses. The forces in major tendons and joint reaction forces were calculated. The components of the joint reaction forces caused by wrapping of tendons around sesamoid bones were found to be of similar magnitude to the reaction forces between the long bones at each joint. This finding highlighted the importance of taking into account muscle-tendon wrapping when evaluating joint loading in the equine distal forelimb

Efficacy and Efficiency of Multivariate Linear Regression for Rapid Prediction of Femoral Strain Fields during Activity

© 2018 IPEM. Published by Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (December 2018) in accordance with the publisher’s archiving policy.Multivariate Linear Regression-based (MLR) surrogate models were explored to reduce the computational cost of predicting femoral strains during normal activity in comparison with finite element analysis. The musculoskeletal model of one individual, the finite-element model of the right femur, and experimental force and motion data for normal walking, fast walking, stair ascent, stair descent, and rising from a chair were obtained from a previous study. Equivalent Von Mises strain was calculated for 1000 frames uniformly distributed across activities. MLR surrogate models were generated using training sets of 50, 100, 200 and 300 samples. The finite-element and MLR analyses were compared using linear regression. The Root Mean Square Error (RMSE) and the 95th percentile of the strain error distribution were used as indicators of average and peak error. The MLR model trained using 200 samples (RMSE < 108 µε; peak error < 228 µε) was used as a reference. The finite-element method required 66 s per frame on a standard desktop computer. The MLR model required 0.1 s per frame plus 1848 s of training time. RMSE ranged from 1.2% to 1.3% while peak error ranged from 2.2% to 3.6% of the maximum micro-strain (5020 µε). Performance within an activity was lower during early and late stance, with RMSE of 4.1% and peak error of 8.6% of the maximum computed micro-strain. These results show that MLR surrogate models may be used to rapidly and accurately estimate strain fields in long bones during daily physical activity

A novel training-free method for real-time prediction of femoral strain

© 2019 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (February 2019) in accordance with the publisher’s archiving policySurrogate methods for rapid calculation of femoral strain are limited by the scope of the training data. We compared a newly developed training-free method based on the superposition principle (Superposition Principle Method, SPM) and popular surrogate methods for calculating femoral strain during activity. Finite-element calculations of femoral strain, muscle, and joint forces for five different activity types were obtained previously. Multi-linear regression, multivariate adaptive regression splines, and Gaussian process were trained for 50, 100, 200, and 300 random samples generated using Latin Hypercube (LH) and Design of Experiment (DOE) sampling. The SPM method used weighted linear combinations of 173 activity-independent finite-element analyses accounting for each muscle and hip contact force. Across the surrogate methods, we found that 200 DOE samples consistently provided low error (RMSE < 100 µε), with model construction time ranging from 3.8 to 63.3 h and prediction time ranging from 6 to 1236 s per activity. The SPM method provided the lowest error (RMSE = 40 µε), the fastest model construction time (3.2 h) and the second fastest prediction time per activity (36 s) after Multi-linear Regression (6 s). The SPM method will enable large numerical studies of femoral strain and will narrow the gap between bone strain prediction and real-time clinical applications

Physical activity when young provides lifelong benefits to cortical bone size and strength in men

The skeleton shows greatest plasticity to physical activity-related mechanical loads during youth but is more at risk for failure during aging. Do the skeletal benefits of physical activity during youth persist with aging? To address this question, we used a uniquely controlled cross-sectional study design in which we compared the throwing-to-nonthrowing arm differences in humeral diaphysis bone properties in professional baseball players at different stages of their careers (n = 103) with dominant-to-nondominant arm differences in controls (n = 94). Throwing-related physical activity introduced extreme loading to the humeral diaphysis and nearly doubled its strength. Once throwing activities ceased, the cortical bone mass, area, and thickness benefits of physical activity during youth were gradually lost because of greater medullary expansion and cortical trabecularization. However, half of the bone size (total cross-sectional area) and one-third of the bone strength (polar moment of inertia) benefits of throwing-related physical activity during youth were maintained lifelong. In players who continued throwing during aging, some cortical bone mass and more strength benefits of the physical activity during youth were maintained as a result of less medullary expansion and cortical trabecularization. These data indicate that the old adage of “use it or lose it” is not entirely applicable to the skeleton and that physical activity during youth should be encouraged for lifelong bone health, with the focus being optimization of bone size and strength rather than the current paradigm of increasing mass. The data also indicate that physical activity should be encouraged during aging to reduce skeletal structural decay

Standardization proposal of soft tissue artefact description for data sharing in human motion measurements

Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications

Targeted physiotherapy for patellofemoral joint osteoarthritis: A protocol for a randomised, single-blind controlled trial

<p>Abstract</p> <p>Background</p> <p>The patellofemoral joint (PFJ) is one compartment of the knee that is frequently affected by osteoarthritis (OA) and is a potent source of OA symptoms. However, there is a dearth of evidence for compartment-specific treatments for PFJ OA. Therefore, this project aims to evaluate whether a physiotherapy treatment, targeted to the PFJ, results in greater improvements in pain and physical function than a physiotherapy education intervention in people with symptomatic and radiographic PFJ OA.</p> <p>Methods</p> <p>90 people with PFJ OA (PFJ-specific history, signs and symptoms and radiographic evidence of PFJ OA) will be recruited from the community and randomly allocated into one of two treatments. A randomised controlled trial adhering to CONSORT guidelines will evaluate the efficacy of physiotherapy (8 individual sessions over 12 weeks, as well as a home exercise program 4 times/week) compared to a physiotherapist-delivered OA education control treatment (8 individual sessions over 12 weeks). Physiotherapy treatment will consist of (i) quadriceps muscle retraining; (ii) quadriceps and hip muscle strengthening; (iii) patellar taping; (iv) manual PFJ and soft tissue mobilisation; and (v) OA education. Resistance and dosage of exercises will be tailored to the participant's functional level and clinical state. Primary outcomes will be evaluated by a blinded examiner at baseline, 12 weeks and 9 months using validated and reliable pain, physical function and perceived global effect scales. All analyses will be conducted on an intention-to-treat basis using linear mixed regression models, including respective baseline scores as a covariate, subjects as a random effect, treatment condition as a fixed factor and the covariate by treatment interaction.</p> <p>Conclusion</p> <p>This RCT is targeting PFJ OA, an important sub-group of knee OA patients, with a specifically designed conservative intervention. The project's outcome will influence PFJ OA rehabilitation, with the potential to reduce the personal and societal burden of this increasing public health problem.</p> <p>Trial Registration</p> <p>Australia New Zealand Clinical Trials Registry ACTRN12608000288325</p

Frank C. Anderson

Most attempts to quantify in vivo muscle forces in humans have combined noninvasive measures of movement with a mathematical theory called optimization. Here, a cost function is hypothesized, and muscle forces are calculated according to the mechanical