Jeffrey A. Reinbolt

Design of patient-specific gait modifications for knee osteoarthritis rehabilitation

Gait modification is a nonsurgical approach for reducing the external knee adduction torque in patients with knee osteoarthritis (OA). The magnitude of the first adduction torque peak in particular is strongly associated with knee OA progression. While toeing out has been shown to reduce the second peak, no clinically realistic gait modifications have been identified that effectively reduce both peaks simultaneously. This study predicts novel patient-specific gait modifications that achieve this goal without changing the foot path. The modified gait motion was designed for a single patient with knee OA using dynamic optimization of a patient-specific, full-body gait model. The cost function minimized the knee adduction torque subject to constraints limiting how much the new gait motion could deviate from the patients normal gait motion. The optimizations predicted a ldquomedial-thrustrdquo gait pattern that reduced the first adduction torque peak between 32% and 54% and the second peak between 34% and 56%. The new motion involved three synergistic kinematic changes: slightly decreased pelvis obliquity, slightly increased leg flexion, and slightly increased pelvis axial rotation. After gait retraining, the patient achieved adduction torque reductions of 39% to 50% in the first peak and 37% to 55% in the second one. These reductions are comparable to those reported after high tibial osteotomy surgery. The associated kinematic changes were consistent with the predictions except for pelvis obliquity, which showed little change. This study demonstrates that it is feasible to design novel patient-specific gait modifications with potential clinical benefit using dynamic optimization of patient-specific, full-body gait models. Further investigation is needed to assess the extent to which similar gait modifications may be effective for other patients with knee OA.

Optimizing whole-body kinematics to minimize valgus knee loading during sidestepping: Implications for ACL injury risk

The kinematic mechanisms associated with elevated externally applied valgus knee moments during non-contact sidestepping and subsequent anterior cruciate ligament (ACL) injury risk are not well understood. To address this issue, the residual reduction algorithm (RRA) in OpenSim was used to create nine subject-specific, full-body (37 degrees of freedom) torque-driven simulations of athletic males performing unplanned sidestep (UnSS) sport tasks. The RRA was used again to produce an optimized kinematic solution with reduced peak valgus knee torques during the weight acceptance phase of stance. Pre-to-post kinematic optimization, mean peak valgus knee moments were significantly reduced by 44.2 Nm (p=0.045). Nine of a possible 37 upper and lower body kinematic changes in all three planes of motion were consistently used during the RRA to decrease peak valgus knee moments. The generalized kinematic strategy used by all nine simulations to reduce peak valgus knee moments and subsequent ACL injury risk during UnSS was to redirect the whole-body center of mass medially, towards the desired direction of travel.

Are Patient-Specific Joint and Inertial Parameters Necessary for Accurate Inverse Dynamics Analyses of Gait?

Variations in joint parameter (JP) values (axis positions and orientations in body segments) and inertial parameter (IP) values (segment masses, mass centers, and moments of inertia) as well as kinematic noise alter the results of inverse dynamics analyses of gait. Three-dimensional linkage models with joint constraints have been proposed as one way to minimize the effects of noisy kinematic data. Such models can also be used to perform gait optimizations to predict post-treatment function given pre-treatment gait data. This study evaluates whether accurate patient-specific JP and IP values are needed in three-dimensional linkage models to produce accurate inverse dynamics results for gait. The study was performed in two stages. First, we used optimization analyses to evaluate whether patient-specific JP and IP values can be calibrated accurately from noisy kinematic data, and second, we used Monte Carlo analyses to evaluate how errors in JP and IP values affect inverse dynamics calculations. Both stages were performed using a dynamic, 27 degrees-of-freedom, full-body linkage model and synthetic (i.e., computer generated) gait data corresponding to a nominal experimental gait motion. In general, JP but not IP values could be found accurately from noisy kinematic data. Root-mean-square (RMS) errors were 3deg and 4 mm for JP values and 1 kg, 22 mm, and 74 500 kg * mm2 for IP values. Furthermore, errors in JP but not IP values had a significant effect on calculated lower-extremity inverse dynamics joint torques. The worst RMS torque error averaged 4% bodyweight * height (BW * H) due to JP variations but less than 0.25% (BW * H) due to IP variations. These results suggest that inverse dynamics analyses of gait utilizing linkage models with joint constraints should calibrate the models JP values to obtain accurate joint torques

Evaluation of a particle swarm algorithm for biomechanical optimization.

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can be affected by scaling to account for design variables with different length scales or units. In this study we evaluate a recently-developed version of the particle swarm optimization (PSO) algorithm to address these problems. The algorithms global search capabilities were investigated using a suite of difficult analytical test problems, while its scale-independent nature was proven mathematically and verified using a biomechanical test problem. For comparison, all test problems were also solved with three off-the-shelf optimization algorithms--a global genetic algorithm (GA) and multistart gradient-based sequential quadratic programming (SQP) and quasi-Newton (BFGS) algorithms. For the analytical test problems, only the PSO algorithm was successful on the majority of the problems. When compared to previously published results for the same problems, PSO was more robust than a global simulated annealing algorithm but less robust than a different, more complex genetic algorithm. For the biomechanical test problem, only the PSO algorithm was insensitive to design variable scaling, with the GA algorithm being mildly sensitive and the SQP and BFGS algorithms being highly sensitive. The proposed PSO algorithm provides a new off-the-shelf global optimization option for difficult biomechanical problems, especially those utilizing design variables with different length scales or units.

Importance of preswing rectus femoris activity in stiff-knee gait.

Stiff-knee gait is characterized by diminished and delayed knee flexion during swing. Rectus femoris transfer surgery, a common treatment for stiff-knee gait, is often recommended when a patient exhibits prolonged activity of the rectus femoris muscle during swing. Treatment outcomes are inconsistent, in part, due to limited understanding of the biomechanical factors contributing to stiff-knee gait. This study used a combination of gait analysis and dynamic simulation to examine how activity of the rectus femoris during swing, and prior to swing, contribute to knee flexion. A group of muscle-actuated dynamic simulations was created that accurately reproduced the gait dynamics of ten subjects with stiff-knee gait. These simulations were used to examine the effects of rectus femoris activity on knee motion by eliminating rectus femoris activity during preswing and separately during early swing. The increase in peak knee flexion by eliminating rectus femoris activity during preswing (7.5+/-3.1 degrees ) was significantly greater on average (paired t-test, p=0.035) than during early swing (4.7+/-3.6 degrees ). These results suggest that preswing rectus femoris activity is at least as influential as early swing activity in limiting the knee flexion of persons with stiff-knee gait. In evaluating rectus femoris activity for treatment of stiff-knee gait, preswing as well as early swing activity should be examined.

Predicting outcomes of rectus femoris transfer surgery

Rectus femoris transfer surgery is a common treatment for stiff knee gait in children with cerebral palsy. Unfortunately, the improvement in knee motion after surgery is inconsistent. There is great interest in understanding the causes of stiff knee gait and determining predictors of improved knee motion after surgery. This study demonstrates that it is possible to predict whether or not a patients knee motion will improve following rectus femoris transfer surgery with greater than 80% accuracy. A predictive model was developed that requires only a few preoperative gait analysis measurements, already collected as a routine part of treatment planning. Our examination of 62 patients before and after rectus femoris transfer revealed that a combination of hip power, knee power, and knee flexion velocity at toe-off correctly predicted postoperative outcome for 80% of cases. With the addition of two more preoperative measurements, hip flexion and internal rotation, prediction accuracy increased to nearly 88%. Other combinations of preoperative gait analysis measurements also predicted outcomes with high accuracy. These results provide insight into factors related to positive outcomes and suggest that predictive models provide a valuable tool for determining indications for rectus femoris transfer.

Elevated gastrocnemius forces compensate for decreased hamstrings forces during the weight-acceptance phase of single-leg jump landing: implications for anterior cruciate ligament injury risk

Approximately 320,000 anterior cruciate ligament (ACL) injuries in the United States each year are non-contact injuries, with many occurring during a single-leg jump landing. To reduce ACL injury risk, one option is to improve muscle strength and/or the activation of muscles crossing the knee under elevated external loading. This studys purpose was to characterize the relative force production of the muscles supporting the knee during the weight-acceptance (WA) phase of single-leg jump landing and investigate the gastrocnemii forces compared to the hamstrings forces. Amateur male Western Australian Rules Football players completed a single-leg jump landing protocol and six participants were randomly chosen for further modeling and simulation. A three-dimensional, 14-segment, 37 degree-of-freedom, 92 muscle-tendon actuated model was created for each participant in OpenSim. Computed muscle control was used to generate 12 muscle-driven simulations, 2 trials per participant, of the WA phase of single-leg jump landing. A one-way ANOVA and Tukey post-hoc analysis showed both the quadriceps and gastrocnemii muscle force estimates were significantly greater than the hamstrings (p<0.001). Elevated gastrocnemii forces corresponded with increased joint compression and lower ACL forces. The elevated quadriceps and gastrocnemii forces during landing may represent a generalized muscle strategy to increase knee joint stiffness, protecting the knee and ACL from external knee loading and injury risk. These results contribute to our understanding of how muscles function during single-leg jump landing and should serve as the foundation for novel muscle-targeted training intervention programs aimed to reduce ACL injuries in sport.

Multiscale modeling in computational biomechanics

Biomechanics is broadly defined as the scientific discipline that investigates the effects of forces acting on and within biological structures. The realm of biomechanics includes the circulatory and respiratory systems, tissue mechanics and mechanotransduction, and the musculoskeletal system and motor control. As in many other biological phenomena, many spatial scales are crossed by biomechanics research: intracellular, multicellular, and extracellular matrices; and tissue, organ, and multiorgan systems. It is well established that the effect of forces at higher scales influence behavior at lower scales and that lower-scale properties influence higher-scale response. However, computational methods that incorporate these interactions in biomechanics are relatively rare. In general, computational models that include representation of multiple spatial or temporal scales are loosely defined as multiscale. The fact that multiscale modeling is not well defined lends the term to a variety of scenarios within the computational physiology community. In biomechanics, multiscale modeling may mean establishing a hierarchical link between the spatial and temporal scales, while the output of a larger-scale system is passed through a finely detailed representation at a lower scale (e.g., body-level movement simulations that provide net joint loading for tissue-level stress analysis). In reality, multiscale modeling may require more intricate representation of interactions among scales. A concurrent simulation strategy is inevitable to adequately represent nonlinear associations that have been known for decades [1].

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLABs variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1s (OpenSim) to 2.9s (MATLAB). For the closed-loop case, a proportional-integral-derivative controller was used to successfully balance a pole on models hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions.

Effects of increased step width on frontal plane knee biomechanics in healthy older adults during stair descent.

BACKGROUND Peak internal knee abduction moment is a common surrogate variable associated with medial compartment knee loading. Stair descent has been shown to yield a greater peak knee abduction moment compared to level-walking. Changes in step width (SW) may lead to changes in frontal plane lower extremity limb alignment in the frontal plane and alter peak knee abduction moment. The purpose of this study was to investigate the effects of increased SW on frontal plane knee biomechanics during stair descent in healthy older adults. METHODS Twenty healthy adults were recruited for the study. A motion analysis system was used to obtain three-dimensional lower limb kinematics during testing. An instrumented 3-step staircase with two additional customized wooden steps was used to collect ground reaction forces (GRF) data during stair descent trials. Participants performed five stair descent trials at their self-selected speed using preferred, wide (26% leg length), and wider (39% leg length) SW. RESULTS The preferred normalized SW in older adults during stair descent was 20% of leg length. Wide and wider SW during stair descent reduced both first and second peak knee adduction angles and abduction moments compared to preferred SW in healthy adults. CONCLUSIONS Increased SW reduced peak knee adduction angles and abduction moments. The reductions in knee abduction moments may have implications in reducing medial compartment knee loads during stair descent.