OpenSim: Simulating musculoskeletal dynamics and neuromuscular control to study human and animal movement.

Movement is fundamental to human and animal life, emerging through interaction of complex neural, muscular, and skeletal systems. Study of movement draws from and contributes to diverse fields, including biology, neuroscience, mechanics, and robotics. OpenSim unites methods from these fields to create fast and accurate simulations of movement, enabling two fundamental tasks. First, the software can calculate variables that are difficult to measure experimentally, such as the forces generated by muscles and the stretch and recoil of tendons during movement. Second, OpenSim can predict novel movements from models of motor control, such as kinematic adaptations of human gait during loaded or inclined walking. Changes in musculoskeletal dynamics following surgery or due to human-device interaction can also be simulated; these simulations have played a vital role in several applications, including the design of implantable mechanical devices to improve human grasping in individuals with paralysis. OpenSim is an extensible and user-friendly software package built on decades of knowledge about computational modeling and simulation of biomechanical systems. OpenSim's design enables computational scientists to create new state-of-the-art software tools and empowers others to use these tools in research and clinical applications. OpenSim supports a large and growing community of biomechanics and rehabilitation researchers, facilitating exchange of models and simulations for reproducing and extending discoveries. Examples, tutorials, documentation, and an active user forum support this community. The OpenSim software is covered by the Apache License 2.0, which permits its use for any purpose including both nonprofit and commercial applications. The source code is freely and anonymously accessible on GitHub, where the community is welcomed to make contributions. Platform-specific installers of OpenSim include a GUI and are available on simtk.org.

Preparatory co-activation of the ankle muscles may prevent ankle inversion injuries.

Ankle inversion sprains are the most frequent acute musculoskeletal injuries occurring in physical activity. Interventions that retrain muscle coordination have helped rehabilitate injured ankles, but it is unclear which muscle coordination strategies, if any, can prevent ankle sprains. The purpose of this study was to determine whether coordinated activity of the ankle muscles could prevent excessive ankle inversion during a simulated landing on a 30° incline. We used a set of musculoskeletal simulations to evaluate the efficacy of two strategies for coordinating the ankle evertor and invertor muscles during simulated landing scenarios: planned co-activation and stretch reflex activation with physiologic latency (60-ms delay). A full-body musculoskeletal model of landing was used to generate simulations of a subject dropping onto an inclined surface with each coordination condition. Within each condition, the intensity of evertor and invertor co-activity or stretch reflexes were varied systematically. The simulations revealed that strong preparatory co-activation of the ankle evertors and invertors prior to ground contact prevented ankle inversion from exceeding injury thresholds by rapidly generating eversion moments after initial contact. Conversely, stretch reflexes were too slow to generate eversion moments before the simulations reached the threshold for inversion injury. These results suggest that training interventions to protect the ankle should focus on stiffening the ankle with muscle co-activation prior to landing. The musculoskeletal models, controllers, software, and simulation results are freely available online at http://simtk.org/home/ankle-sprains, enabling others to reproduce the results and explore new injury scenarios and interventions.

Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait.

OBJECTIVE: Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. METHODS: Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. RESULTS: Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. CONCLUSION: These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. SIGNIFICANCE: The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations.

How tibiofemoral alignment and contact locations affect predictions of medial and lateral tibiofemoral contact forces.

Understanding degeneration of biological and prosthetic knee joints requires knowledge of the in-vivo loading environment during activities of daily living. Musculoskeletal models can estimate medial/lateral tibiofemoral compartment contact forces, yet anthropometric differences between individuals make accurate predictions challenging. We developed a full-body OpenSim musculoskeletal model with a knee joint that incorporates subject-specific tibiofemoral alignment (i.e. knee varus-valgus) and geometry (i.e. contact locations). We tested the accuracy of our model and determined the importance of these subject-specific parameters by comparing estimated to measured medial and lateral contact forces during walking in an individual with an instrumented knee replacement and post-operative genu valgum (6°). The errors in the predictions of the first peak medial and lateral contact force were 12.4% and 11.9%, respectively, for a model with subject-specific tibiofemoral alignment and contact locations determined through radiographic analysis, vs. 63.1% and 42.0%, respectively, for a model with generic parameters. We found that each degree of tibiofemoral alignment deviation altered the first peak medial compartment contact force by 51N (r(2)=0.99), while each millimeter of medial-lateral translation of the compartment contact point locations altered the first peak medial compartment contact force by 41N (r(2)=0.99). The model, available at www.simtk.org/home/med-lat-knee/, enables the specification of subject-specific joint alignment and compartment contact locations to more accurately estimate medial and lateral tibiofemoral contact forces in individuals with non-neutral alignment.

Changes in tibiofemoral forces due to variations in muscle activity during walking.

Muscles induce large forces in the tibiofemoral joint during walking and thereby influence the health of tissues like articular cartilage and menisci. It is possible to walk with a wide variety of muscle coordination patterns, but the effect of varied muscle coordination on tibiofemoral contact forces remains unclear. The goal of this study was to determine the effect of varied muscle coordination on tibiofemoral contact forces. We developed a musculoskeletal model of a subject walking with an instrumented knee implant. Using an optimization framework, we calculated the tibiofemoral forces resulting from muscle coordination that reproduced the subject's walking dynamics. We performed a large set of optimizations in which we systematically varied the coordination of muscles to determine the influence on tibiofemoral force. Model-predicted tibiofemoral forces arising with minimum muscle activation matched in vivo forces measured during early stance, but were greater than in vivo forces during late stance. Peak tibiofemoral forces during late stance could be reduced by increasing the activation of the gluteus medius, uniarticular hip flexors, and soleus, and by decreasing the activation of the gastrocnemius and rectus femoris. These results suggest that retraining of muscle coordination could substantially reduce tibiofemoral forces during late stance.

The effects of walking speed on tibiofemoral loading estimated via musculoskeletal modeling.

Net muscle moments (NMMs) have been used as proxy measures of joint loading, but musculoskeletal models can estimate contact forces within joints. The purpose of this study was to use a musculoskeletal model to estimate tibiofemoral forces and to examine the relationship between NMMs and tibiofemoral forces across walking speeds. We collected kinematic, kinetic, and electromyographic data as ten adult participants walked on a dual-belt force-measuring treadmill at 0.75, 1.25, and 1.50 m/s. We scaled a musculoskeletal model to each participant and used OpenSim to calculate the NMMs and muscle forces through inverse dynamics and weighted static optimization, respectively. We determined tibiofemoral forces from the vector sum of intersegmental and muscle forces crossing the knee. Estimated tibiofemoral forces increased with walking speed. Peak early-stance compressive tibiofemoral forces increased 52% as walking speed increased from 0.75 to 1.50 m/s, whereas peak knee extension NMMs increased by 168%. During late stance, peak compressive tibiofemoral forces increased by 18% as speed increased. Although compressive loads at the knee did not increase in direct proportion to NMMs, faster walking resulted in greater compressive forces during weight acceptance and increased compressive and anterior/posterior tibiofemoral loading rates in addition to a greater abduction NMM.

Consistency among musculoskeletal models: caveat utilitor.

Musculoskeletal simulation software and model repositories have broadened the user base able to perform musculoskeletal analysis and have facilitated in the sharing of models. As the recognition of musculoskeletal modeling continues to grow as an engineering discipline, the consistency in results derived from different models and software is becoming more critical. The purpose of this study was to compare eight models from three software packages and evaluate differences in quadriceps moment arms, predicted muscle forces, and predicted tibiofemoral contact forces for an idealized knee-extension task spanning -125 to +10° of knee extension. Substantial variation among models was observed for the majority of aspects evaluated. Differences among models were influenced by knee angle, with better agreement of moment arms and tibiofemoral joint contact force occurring at low to moderate knee flexion angles. The results suggest a lack of consistency among models and that output differences are not simply an artifact of naturally occurring inter-individual differences. Although generic musculoskeletal models can easily be scaled to consistent limb lengths and use the same muscle recruitment algorithm, the results suggest those are not sufficient conditions to produce consistent muscle or joint contact forces, even for simplified models with no potential of co-contraction.

Compressive tibiofemoral force during crouch gait.

Crouch gait, a common walking pattern in individuals with cerebral palsy, is characterized by excessive flexion of the hip and knee. Many subjects with crouch gait experience knee pain, perhaps because of elevated muscle forces and joint loading. The goal of this study was to examine how muscle forces and compressive tibiofemoral force change with the increasing knee flexion associated with crouch gait. Muscle forces and tibiofemoral force were estimated for three unimpaired children and nine children with cerebral palsy who walked with varying degrees of knee flexion. We scaled a generic musculoskeletal model to each subject and used the model to estimate muscle forces and compressive tibiofemoral forces during walking. Mild crouch gait (minimum knee flexion 20-35°) produced a peak compressive tibiofemoral force similar to unimpaired walking; however, severe crouch gait (minimum knee flexion>50°) increased the peak force to greater than 6 times body-weight, more than double the load experienced during unimpaired gait. This increase in compressive tibiofemoral force was primarily due to increases in quadriceps force during crouch gait, which increased quadratically with average stance phase knee flexion (i.e., crouch severity). Increased quadriceps force contributes to larger tibiofemoral and patellofemoral loading which may contribute to knee pain in individuals with crouch gait.