Minimal formulation of joint motion for biomechanisms

A scoping review and evaluation of open-source transtibial amputation musculoskeletal models for female populations

Musculoskeletal modeling is often used to study people with transtibial amputations. Females in this population are of particular interest as they are underrepresented in research, experience unique challenges, and demonstrate gait biomechanics distinct from males. Because generic models often neglect innate variations between populations, it is important to determine whether data used to develop a model are representative of the population studied. The objective of this study was to review and analyze existing transtibial amputation musculoskeletal models, establish a database from the information compiled, and use the database to select the model most relevant for studying female populations. A scoping search was performed and a database was created based on data detailing the eligible models. Models were evaluated through a weighted decision process based on criteria of their representation of females with transtibial amputations, prosthetic functionality, development transparency, overall functionality, and experimental validation methods. The scoping review identified 3 studies, Willson et al., LaPrè et al., and Miller and Esposito. A database detailing these models was established. The Willson model scored highest on all criteria except overall functionality, where the LaPrè model outscored it. Based on the established weightings, the Willson model was classed most appropriate for the stated goals. The created database can be used by other researchers to guide their own modeling studies, irrespective of the population of focus. Of the 3, the Willson model was found most relevant for studying females with transtibial amputations. This model will be used in future work investigating and addressing challenges of females with transtibial amputations.

Influence of multibody kinematic optimisation pipeline on marker residual errors

Residual errors are used as a goodness-of-fit metric of the musculoskeletal model to the experimental data in multibody kinematic optimisation (MKO) analyses. Despite many studies reporting residual errors as a criterion for evaluating their proposed algorithm or model, the validity of residual errors as a performance metric has been questioned, with studies indicating a non-causal relationship between residual errors and computed joint angles. Additionally, the impact of different parameters of an MKO pipeline on residual errors has not been analysed. In our study, we have investigated the effect of each step of the MKO pipeline on residual errors, and the existence of a causal relationship between residual errors and joint angles. Increases in residual errors from the baseline model (13.84 [12.72, 15.15]mm) were obtained for: models with marker registration errors of 1.25 cm (16.36 [15.37, 17.57]mm); models with segment scaling errors of 1.25 cm (14.84 [13.77, 16.24]mm); variation in marker weighting scheme (15.28[14.00, 16.85]mm); and models with differing joint constraints (18.21[17.37, 19.11]mm). We also observed that significant variation in residual errors results in significant variation in computed joint angles, with increases in residual error positively correlated with increases in joint angle errors when the same MKO pipeline is employed. Our findings support the existence of a causal relationship and present the significant effect the MKO pipeline has on residual errors. We believe our results can further the discussion of residual errors as a goodness-of-fit metric, specifically in the absence of artefact-free bone movement.

MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks

Artificial neural networks (ANNs) are a powerful class of computational models for unravelling neural mechanisms of brain function. However, for neural control of movement, they currently must be integrated with software simulating biomechanical effectors, leading to limiting impracticalities: (1) researchers must rely on two different platforms and (2) biomechanical effectors are not generally differentiable, constraining researchers to reinforcement learning algorithms despite the existence and potential biological relevance of faster training methods. To address these limitations, we developed MotorNet, an open-source Python toolbox for creating arbitrarily complex, differentiable, and biomechanically realistic effectors that can be trained on user-defined motor tasks using ANNs. MotorNet is designed to meet several goals: ease of installation, ease of use, a high-level user-friendly application programming interface, and a modular architecture to allow for flexibility in model building. MotorNet requires no dependencies outside Python, making it easy to get started with. For instance, it allows training ANNs on typically used motor control models such as a two joint, six muscle, planar arm within minutes on a typical desktop computer. MotorNet is built on PyTorch and therefore can implement any network architecture that is possible using the PyTorch framework. Consequently, it will immediately benefit from advances in artificial intelligence through PyTorch updates. Finally, it is open source, enabling users to create and share their own improvements, such as new effector and network architectures or custom task designs. MotorNet's focus on higher-order model and task design will alleviate overhead cost to initiate computational projects for new researchers by providing a standalone, ready-to-go framework, and speed up efforts of established computational teams by enabling a focus on concepts and ideas over implementation.

Comparison of biomechanical analysis results using different musculoskeletal models for children with cerebral palsy

Introduction: Musculoskeletal model-based simulations have gained popularity as a tool for analyzing human movement biomechanics. However, when examining the same gait, different models with varying anatomical data and assumptions may produce inconsistent biomechanical results. This inconsistency is particularly relevant for children with cerebral palsy, who often exhibit multiple pathological gait patterns that can impact model outputs. Methods: The aim of this study was to investigate the effect of selecting musculoskeletal models on the biomechanical analysis results in children with cerebral palsy. Gait data were collected from multiple participants at slow, medium, and fast velocities. Joint kinematics, joint dynamics, and muscle activation were calculated using six popular musculoskeletal models within a biomechanical simulation environment. Results: The degree of inconsistency, measured as the root-mean-square deviation, in kinematic and kinetic results produced by the different models ranged from 4% to 40% joint motion range and 0%-28% joint moment range, respectively. The correlation between the results of the different models (both kinematic and kinetic) was good (R> 0.85, P < 0.01), with a stronger correlation observed in the kinetic results. Four of the six models showed a positive correlation between the simulated muscle activation of rectus femoris and the surface EMG, while all models exhibited a positive correlation between the activation of medial gastrocnemius and the surface EMG (P < 0.01). Discussion: These results provide insights into the consistency of model results, factors influencing consistency, characteristics of each model's outputs, mechanisms underlying these characteristics, and feasible applications for each model. By elucidating the impact of model selection on biomechanical analysis outcomes, this study advances the field's understanding of musculoskeletal modeling and its implications for clinical gait analysis model decision-making in children with cerebral palsy.

A Shoulder Musculoskeletal Model with Three-Dimensional Complex Muscle Geometries

Muscle structure is an essential component in typical computational models of the musculoskeletal system. Almost all musculoskeletal models represent muscle geometry using a set of line segments. The straight-line approach limits models' ability to accurately predict the paths of muscles with complex geometry. This approach needs knowledge of how the muscle changes shape and interacts with fundamental structures like muscles, bones, and joints that move. Moreover, the moment arms are supposed to be equivalent to all the fibers in the muscle. This study aims to create a shoulder musculoskeletal model that includes complex muscle geometries. We reconstructed the shape of fibers in the entire volume of six muscles adjacent to the shoulder using an automated technique. This method generates many fibers from the surface geometry of the skeletal muscle and its attachment areas. Highly discretized muscle representations for all muscles were created and used to simulate different shoulder movements. The moment arms of each muscle were calculated and validated against cadaveric measurements and models of the same muscles from the literature. We found that simulations using the developed musculoskeletal models generated more realistic geometries, which expands the physical representation of muscles compared to line segments. The shoulder musculoskeletal model with complex muscle geometry is created to increase the anatomical reality of models and the lines action of muscle fibers, and to be used for finite element investigations.

Real-Time Identification of Wrist Kinematics via Sparsity-Promoting Extended Kalman Filter Based on Ellipsoidal Joint Formulation

This paper proposes a novel method for real-time wrist kinematics identification. Method: We design the wrist kinematics regression model following a novel ellipsoidal joint formulation, which features a quaternion-based rotation constraint and 2-dimensional Fourier linear combiners (FLC) to approximate the coupled rotations and translational displacements of the wrist. Extended Kalman Filter (EKF) is then implemented to update the model in real-time. However, unlike previous studies, here we introduce a sparsity-promoting feature in the model regression through the optimality of EKF by designing a smooth 1-minimization observation function. This is done to ensure the best identification of key parameters, and to improve the robustness of regression under noisy conditions. Results: Simulations employ multiple reference models to evaluate the performance of the proposed approach. Experiments are later carried out on motion data collected by a lab-developed wrist kinematics measurement tool. Both simulation and experiment show that the proposed approach can robustly identify the wrist kinematics in real-time. Conclusion: The findings confirm that the proposed regression model combined with the sparsity-promoting EKF is reliable in the real-time modeling of wrist kinematics. Significance: The proposed method can be applied to generic wrist kinematics modeling problems, and utilized in the control system of wearable wrist exoskeletons. The framework of the proposed method may also be applied to real-time identification of other joints for exoskeleton control.

Simulating the evolution of bipedalism and the absence of static bipedal hexapods

In nature, very few animals locomote on two legs. Static bipedalism can be found in four limbed and five limbed animals like dogs, cats, birds, monkeys and kangaroos, but it cannot be seen in hexapods or other multi-limbed animals. In this paper, we present a simulation with a novel perspective on the evolution of static bipedalism, with a virtual creature evolving its body and controllers, and we apply an evolutionary algorithm to explore the locomotion transition from octapods to bipods. We find that the presence of four limbs in the evolutionary trajectory of the creature scaffolds a parametric jump that enables bipedalism, and shows that hexapods, without undergoing such transformation, struggle to evolve into bipeds. An analysis of the transitional parameters points to the role of a shorter femur length in helping maintain the stability of the body, and the tibia length is responsible for improving the forward speed.

Robosample: A rigid-body molecular simulation program based on robot mechanics

BACKGROUND

Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to increase configuration space sampling in molecular simulations.

METHODS

Here, we introduce Robosample, a software package that implements high-performance constrained dynamics algorithms, originally developed for robotics, and applies them to simulations of biomolecular systems. As in the gMolmodel package developed by Spiridon and Minh in 2017, Robosample uses Constrained Dynamics Hamiltonian Monte Carlo (CDHMC) as a Gibbs sampling move - a type of Monte Carlo move where a subset of coordinates is allowed to change. In addition to the previously described Cartesian and torsional dynamics moves, Robosample implements spherical and cylindrical joints that can be distributed along the molecule by the user.

RESULTS

In alanine dipeptide simulations, the free energy surface is recovered by mixing fully flexible with torsional, cylindrical, or spherical dynamics moves. Ramachandran dynamics, where only the two key torsions are mobile, accelerate the slowest transition by an order of magnitude. We also show that simulations of a complex glycan cover significantly larger regions of the configuration space when mixed with constrained dynamics.

MAJOR CONCLUSIONS

Robosample is a tool of choice for efficient conformational sampling of large biomolecules.

GENERAL SIGNIFICANCE

Robosample is intended as a reliable and user-friendly simulation package for fast biomolecular sampling that does not require extensive expertise in mechanical engineering or in the statistical mechanics of reduced coordinates.

Comparison of shoulder kinematic chain models and their influence on kinematics and kinetics in the study of manual wheelchair propulsion

Several kinematic chains of the upper limbs have been designed in musculoskeletal models to investigate various upper extremity activities, including manual wheelchair propulsion. The aim of our study was to compare the effect of an ellipsoid mobilizer formulation to describe the motion of the scapulothoracic joint with respect to regression-based models on shoulder kinematics, shoulder kinetics and computational time, during manual wheelchair propulsion activities. Ten subjects, familiar with manual wheelchair propulsion, were equipped with reflective markers and performed start-up and propulsion cycles with an instrumented field wheelchair. Kinematic data obtained from the optoelectronic system and kinetic data measured by the sensors on the wheelchair were processed using the OpenSim software with three shoulder joint modeling versions (ellipsoid mobilizer, regression equations or fixed scapula) of an upper-limb musculoskeletal model. As expected, the results obtained with the three versions of the model varied, for both segment kinematics and shoulder kinetics. With respect to the model based on regression equations, the model describing the scapulothoracic joint as an ellipsoid could capture the kinematics of the upper limbs with higher fidelity. In addition, the mobilizer formulation allowed to compute consistent shoulder moments at a low computer processing cost. Further developments should be made to allow a subject-specific definition of the kinematic chain.

On the influence of the shoulder kinematic chain on joint kinematics and musculotendon lengths during wheelchair propulsion estimated from multibody kinematics optimization

Multibody kinematic optimization is frequently used to assess shoulder kinematics during manual wheelchair (MWC) propulsion but multiple kinematics chains are available. It is hypothesized that these different kinematic chains affect marker tracking, shoulder kinematics and resulting musculotendon (MT) lengths. In this study, shoulder kinematics and MT lengths obtained from four shoulder kinematic chains (open-loop thorax-clavicle-scapula-humerus (M1), closed-loop with contact ellipsoid (M2), scapula rhythm from regression equations (M3), and a single ball-and- socket joint between the thorax and the humerus (M4) were compared. Right-side shoulder kinematics from seven subjects were obtained with 34 reflective markers and a scapula locator using an optoelectronic motion capture system while propelling on a MWC simulator. Data was processed based on the four models. Results showed the impact of shoulder kinematic chains on all studied variables. Marker reconstruction errors were found similar between M1 and M2 and lower than for M3 and M4. Few degrees of freedom (DoF) were noticeably different between M1 and M2, but all shoulder DoFs were significantly affected between M1 and M4. As a consequence of differences in joint kinematics, MT lengths were affected by the kinematic chain definition. The contact ellipsoid (M2) was found as a good trade-off between marker tracking and penetration avoidance of the scapula. The regression-based model (M3) was less efficient due to limited humerus elevation during MWC propulsion, as well as the ball-and-socket model (M4) which appeared not suitable for upper limbs activities, including MWC propulsion.

Cortical and subcortical areas involved in the regulation of reach movement speed in the human brain: An fMRI study

Reach movements are characterized by multiple kinematic variables that can change with age or due to medical conditions such as movement disorders. While the neural control of reach direction is well investigated, the elements of the neural network regulating speed (the nondirectional component of velocity) remain uncertain. Here, we used a custom made magnetic resonance (MR)-compatible arm movement tracking system to capture the real kinematics of the arm movements while measuring brain activation with functional magnetic resonance imaging to reveal areas in the human brain in which BOLD-activation covaries with the speed of arm movements. We found significant activation in multiple cortical and subcortical brain regions positively correlated with endpoint (wrist) speed (speed-related activation), including contralateral premotor cortex (PMC), supplementary motor area (SMA), thalamus (putative VL/VA nuclei), and bilateral putamen. The hand and arm regions of primary sensorimotor cortex (SMC) and a posterior region of thalamus were significantly activated by reach movements but showed a more binary response characteristics (movement present or absent) than with continuously varying speed. Moreover, a subregion of contralateral SMA also showed binary movement activation but no speed-related BOLD-activation. Effect size analysis revealed bilateral putamen as the most speed-specific region among the speed-related clusters whereas primary SMC showed the strongest specificity for movement versus non-movement discrimination, independent of speed variations. The results reveal a network of multiple cortical and subcortical brain regions that are involved in speed regulation among which putamen, anterior thalamus, and PMC show highest specificity to speed, suggesting a basal-ganglia-thalamo-cortical loop for speed regulation.

On the coordination of highly dynamic human movements: an extension of the Uncontrolled Manifold approach applied to precision jump in parkour

The human body generally has more degrees of freedom than necessary for generating a given movement. According to the motor abundance principle, this redundancy is beneficial as it provides the central nervous system with flexibility and robustness for the generation of movements. Under the hypothesis of the Uncontrolled Manifold, the additional degrees of freedom are used to produce motor solutions by reducing the variability that affects the motion performance across repetitions. In this paper, we present a general mathematical framework derived from robotics to formulate kinematic and dynamic tasks in human movement. On this basis, an extension of the Uncontrolled Manifold approach is introduced to deal with dynamic movements. This extension allows us to present a complex experimental application of the proposed framework to highly dynamic task variables in parkour movements. This experiment involves dynamic tasks expressed in terms of linear and angular momenta. The results show that the central nervous system is able to coordinate such skilled tasks which appear to be preferentially controlled and hierarchically organized. The proposed extension is promising for the study of motion generation in anthropomorphic systems and provides a formal description to investigate kinematics and dynamics tasks in human motions.

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.

OpenSim as a preliminary kinematic testing platform for the development of total knee arthroplasty implants

The design of a total knee replacement implant needs to take account the complex surfaces of the knee which it is replacing. Ensuring design performance of the implant requires in vitro testing of the implant. A considerable amount of time is required to produce components and evaluate them inside an experimental setting. Numerous adjustments in the design of an implant and testing each individual design can be time consuming and expensive. Our solution is to use the OpenSim simulation software to rapidly test multiple design configurations of implants. This study modeled a testing rig which characterized the motion and laxity of knee implants. Three different knee implant designs were used to test and validate the accuracy of the simulation: symmetrical, asymmetric, and anatomic. Kinematics were described as distances measured from the center of each femoral condyle to a plane intersecting the most posterior points of the tibial condyles between 0 and 135° of flexion with 15° increments. Excluding the initial flexion measurement (∼0°) results, the absolute differences between all experimental and simulation results (neutral path, anterior-posterior shear, internal-external torque) for the symmetric, asymmetric, and anatomical designs were 1.98 mm ± 1.15, 1.17 mm ± 0.89, and 1.24 mm ± 0.97, respectively. Considering all designs, the accuracy of the simulation across all tests was 1.46 mm ± 1.07. It was concluded that the results of the simulation were an acceptable representation of the testing rig and hence applicable as a design tool for new total knees.

Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation

Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading.

Construction of a biomechanical head and neck motion model as a guide to evaluation of deformable image registration

The use of deformable image registration methods in the context of adaptive radiotherapy leads to uncertainties in the simulation of the administered dose distributions during the treatment course. Evaluation of these methods is a prerequisite to decide if a plan adaptation will improve the individual treatment. Current approaches using manual references limit the validity of evaluation, especially for low-contrast regions. In particular, for the head and neck region, the highly flexible anatomy and low soft tissue contrast in control images pose a challenge to image registration and its evaluation. Biomechanical models promise to overcome this issue by providing anthropomorphic motion modelling of the patient. We introduce a novel biomechanical motion model for the generation and sampling of different postures of the head and neck anatomy. Motion propagation behaviour of the individual bones is defined by an underlying kinematic model. This model interconnects the bones by joints and thus is capable of providing a wide range of motion. Triggered by the motion of the individual bones, soft tissue deformation is described by an extended heterogeneous tissue model based on the chainmail approach. This extension, for the first time, allows the propagation of decaying rotations within soft tissue without the necessity for explicit tissue segmentation. Overall motion simulation and sampling of deformed CT scans including a basic noise model is achieved within 30 s. The proposed biomechanical motion model for the head and neck site generates displacement vector fields on a voxel basis, approximating arbitrary anthropomorphic postures of the patient. It was developed with the intention of providing input data for the evaluation of deformable image registration.

An MR-compatible gyroscope-based arm movement tracking system

BACKGROUND

Functional magnetic resonance imaging is well suited to link neural population activation with movement parameters of complex natural arm movements. However, currently existing MR-compatible arm tracking devices are not constructed to measure arm joint movement parameters of unrestricted movements. Therefore, to date most research focuses on simple arm movements or includes very little knowledge about the actual movement kinematics.

NEW METHOD

We developed a low cost gyroscope-based arm movement tracking system (GAMTS) that features MR-compatibility. The system consists of dual-axis analogue gyroscopes that measure rotations of upper and lower arm joints. After MR artifact reduction, the rotation angles of the individual arm joints are calculated and used to animate a realistic arm model that is implemented in the OpenSim platform. The OpenSim platform can then provide the kinematics of any point on the arm model.

RESULTS

In order to demonstrate the capabilities of the system, we first assessed the quality of reconstructed wrist movements in a low-noise environment where typical MR-related problems are absent and finally, we validated the reconstruction in the MR environment.

COMPARISON WITH EXISTING METHODS

The system provides the kinematics of the whole arm when natural unrestricted arm movements are performed inside the MR-scanner.

CONCLUSION

The GAMTS is reliably capable of reconstructing the kinematics of trajectories and the reconstruction error is small in comparison with the movement induced variation of speed, displacement, and rotation. Moreover, the system can be used to probe brain areas for their correlation with movement kinematics.

Tibiofemoral contact forces during walking, running and sidestepping

We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20<Radj(2)<0.78), but were variable across gait tasks. Step-wise regression equations from a particular gait task (e.g. walking) produced large errors when applied to a different gait task (e.g. running or sidestepping). Muscles well stabilized the knee, increasing their role in stabilization from walking to running to sidestepping. KAM was a poor predictor of medial contact force and load distributions. Step-wise regression models results suggest the relationships between external gait measures and contact forces cannot be generalized across tasks. Neuromusculoskeletal modelling may be required to examine tibiofemoral contact forces and role of muscle in knee stabilization across gait tasks.

Anterior cruciate ligament (ACL) loading in a collegiate athlete during sidestep cutting after ACL reconstruction: A case study

BACKGROUND

Athletes with anterior cruciate ligament (ACL) injuries usually undergo ACL-reconstruction (ACLR) in order to restore joint stability, so that dynamic maneuvers such as the sidestep cut can be performed. Despite restoration of joint stability after ACLR, many athletes do not return to pre-injury levels and may be at a high risk of a second ACL injury. The purpose of this study was to determine whether or not ACL loading, would increase after ACLR.

METHODS

One female Division I collegiate athlete performed bilateral unanticipated sidestep cuts both before ACL injury and 27months after ACLR. Musculoskeletal simulations were used to calculate ACL loading during the deceleration phase of the sidestep cuts.

RESULTS

Twenty-seven months after ACLR, the athlete demonstrated higher total ACL loading in the ipsilateral limb as well as altered joint kinematics, moments, and quadriceps muscle force production. In the contralateral limb, there were no increases in total ACL loading or muscle force production yet altered lower extremity joint kinematics and moments were present after ACLR.

CONCLUSIONS

Higher total ACL loading in the ipsilateral limb of this athlete may suggest an increased risk of second ACL injury. The results of this study provide an initial step in understanding the effects of ACLR on the risk of second ACL injury in an elite athlete and suggest that it is important to develop a better understanding of this surgical intervention on knee joint loading, in order to reduce the risk of second ACL injury while performing dynamic maneuvers.

A Biomechanical Model of the Scapulothoracic Joint to Accurately Capture Scapular Kinematics during Shoulder Movements

The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models.

An Open-Source Toolbox for Surrogate Modeling of Joint Contact Mechanics

GOAL

Incorporation of elastic joint contact models into simulations of human movement could facilitate studying the interactions between muscles, ligaments, and bones. Unfortunately, elastic joint contact models are often too expensive computationally to be used within iterative simulation frameworks. This limitation can be overcome by using fast and accurate surrogate contact models that fit or interpolate input-output data sampled from existing elastic contact models. However, construction of surrogate contact models remains an arduous task. The aim of this paper is to introduce an open-source program called Surrogate Contact Modeling Toolbox (SCMT) that facilitates surrogate contact model creation, evaluation, and use.

METHODS

SCMT interacts with the third-party software FEBio to perform elastic contact analyses of finite-element models and uses MATLAB to train neural networks that fit the input-output contact data. SCMT features sample point generation for multiple domains, automated sampling, sample point filtering, and surrogate model training and testing.

RESULTS

An overview of the software is presented along with two example applications. The first example demonstrates creation of surrogate contact models of artificial tibiofemoral and patellofemoral joints and evaluates their computational speed and accuracy, while the second demonstrates the use of surrogate contact models in a forward dynamic simulation of an open-chain leg extension-flexion motion.

CONCLUSION

SCMT facilitates the creation of computationally fast and accurate surrogate contact models. Additionally, it serves as a bridge between FEBio and OpenSim musculoskeletal modeling software.

SIGNIFICANCE

Researchers may now create and deploy surrogate models of elastic joint contact with minimal effort.

Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement

Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables researchers and clinicians to study the complex dynamics underlying human and animal movement. NMS models use equations derived from physical laws and biology to help solve challenging real-world problems, from designing prosthetics that maximize running speed to developing exoskeletal devices that enable walking after a stroke. NMS modeling and simulation has proliferated in the biomechanics research community over the past 25 years, but the lack of verification and validation standards remains a major barrier to wider adoption and impact. The goal of this paper is to establish practical guidelines for verification and validation of NMS models and simulations that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies. In particular, we review a general process for verification and validation applied to NMS models and simulations, including careful formulation of a research question and methods, traditional verification and validation steps, and documentation and sharing of results for use and testing by other researchers. Modeling the NMS system and simulating its motion involves methods to represent neural control, musculoskeletal geometry, muscle-tendon dynamics, contact forces, and multibody dynamics. For each of these components, we review modeling choices and software verification guidelines; discuss variability, errors, uncertainty, and sensitivity relationships; and provide recommendations for verification and validation by comparing experimental data and testing robustness. We present a series of case studies to illustrate key principles. In closing, we discuss challenges the community must overcome to ensure that modeling and simulation are successfully used to solve the broad spectrum of problems that limit human mobility.

A new description of scapulothoracic motion during arm movements in healthy subjects

The participation of scapula motion in arm movement is clinically well known and recent three dimensional (3D) analyses using kinematic techniques have confirmed its importance. Scapular motion relative to the thorax has a theoretical maximum of 6 degrees of freedom (DoF), resulting from rotations at both clavicular joints (3 rotational DoF each). However, most recent kinematic studies have only analysed the 3D rotations of the scapula relative to the thorax. In the present study, the 3D translations of the barycentre of the scapula were considered in order to complete the description of movement at the shoulder complex. Eight healthy subjects performed arm elevation in the sagittal and frontal planes, simulated activities of daily living (hair combing and back washing) and maximum voluntary scapula movement (forward and backward rolling). Measurements were recorded using a 6 DoF electromagnetic device and the acromial method of analysis was used. The results showed that 3D scapular rotations and translation of its barycentre were functionally consistent for all tasks. A principal component analysis (PCA) yielded three factors, explaining 97.6% of the variance. The first two factors (protraction and shrug, according to clinical descriptions) combined rotations and translations, consistent with the hypothesis that the scapula rolls over the curved thoracic surface. The third factor related to lateral-medial rotation, thus representing rotation in the plane tangential to the thorax. The PCA suggested that scapular motion can be described using these 3 DoF. This should be studied in a larger group of individuals, including patients with pathological conditions.

WHAT IS A MOMENT ARM? CALCULATING MUSCLE EFFECTIVENESS IN BIOMECHANICAL MODELS USING GENERALIZED COORDINATES

Biomechanics researchers often use multibody models to represent biological systems. However, the mapping from biology to mechanics and back can be problematic. OpenSim is a popular open source tool used for this purpose, mapping between biological specifications and an underlying generalized coordinate multibody system called Simbody. One quantity of interest to biomechanical researchers and clinicians is "muscle moment arm," a measure of the effectiveness of a muscle at contributing to a particular motion over a range of configurations. OpenSim can automatically calculate these quantities for any muscle once a model has been built. For simple cases, this calculation is the same as the conventional moment arm calculation in mechanical engineering. But a muscle may span several joints (e.g., wrist, neck, back) and may follow a convoluted path over various curved surfaces. A biological joint may require several bodies or even a mechanism to accurately represent in the multibody model (e.g., knee, shoulder). In these situations we need a careful definition of muscle moment arm that is analogous to the mechanical engineering concept, yet generalized to be of use to biomedical researchers. Here we present some biomechanical modeling challenges and how they are resolved in OpenSim and Simbody to yield biologically meaningful muscle moment arms.

Hamstrings and quadriceps muscle contributions to energy generation and dissipation at the knee joint during stance, swing and flight phases of level running

BACKGROUND

Human movements involve the generation and dissipation of mechanical energy at the lower extremity joints. However, it is unclear how the individual knee muscles contribute to the energetics during running.

OBJECTIVE

This study aimed to determine how each hamstring and quadricep muscle generates and dissipates energy during stance, swing and flight phases of running.

METHODS

A three-dimensional lower extremity musculoskeletal model was used to estimate the energetics of the individual hamstrings (semimembranosus, semitendinosus, biceps femoris long and short-heads) and quadriceps (rectus femoris, vastus medialis, vastus intermedius and vastus lateralis) muscles for a male subject during level running on a treadmill at a speed of 3.96 m/s.

RESULTS

Our findings demonstrated that the knee flexors generated energy during stance phase and dissipated energy during swing phase, while the knee extensors dissipated energy during the flexion mode of both stance and swing phases, and generated energy during the extension mode. During flight phase, the knee flexors generated energy during the flight phase transiting from toe-off to swing, while the knee extensors generated energy during the flight phase transiting from swing to heel-strike.

CONCLUSION

Individual knee flexors and extensors in the hamstrings and quadriceps play important roles in knee joint energetics, which are necessary for proper execution and stabilization of the stance, swing and flight phases of running.

Muscular strategy shift in human running: dependence of running speed on hip and ankle muscle performance

Humans run faster by increasing a combination of stride length and stride frequency. In slow and medium-paced running, stride length is increased by exerting larger support forces during ground contact, whereas in fast running and sprinting, stride frequency is increased by swinging the legs more rapidly through the air. Many studies have investigated the mechanics of human running, yet little is known about how the individual leg muscles accelerate the joints and centre of mass during this task. The aim of this study was to describe and explain the synergistic actions of the individual leg muscles over a wide range of running speeds, from slow running to maximal sprinting. Experimental gait data from nine subjects were combined with a detailed computer model of the musculoskeletal system to determine the forces developed by the leg muscles at different running speeds. For speeds up to 7 m s(-1), the ankle plantarflexors, soleus and gastrocnemius, contributed most significantly to vertical support forces and hence increases in stride length. At speeds greater than 7 m s(-1), these muscles shortened at relatively high velocities and had less time to generate the forces needed for support. Thus, above 7 m s(-1), the strategy used to increase running speed shifted to the goal of increasing stride frequency. The hip muscles, primarily the iliopsoas, gluteus maximus and hamstrings, achieved this goal by accelerating the hip and knee joints more vigorously during swing. These findings provide insight into the strategies used by the leg muscles to maximise running performance and have implications for the design of athletic training programs.

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.

Simbody: multibody dynamics for biomedical research

Multibody software designed for mechanical engineering has been successfully employed in biomedical research for many years. For real time operation some biomedical researchers have also adapted game physics engines. However, these tools were built for other purposes and do not fully address the needs of biomedical researchers using them to analyze the dynamics of biological structures and make clinically meaningful recommendations. We are addressing this problem through the development of an open source, extensible, high performance toolkit including a multibody mechanics library aimed at the needs of biomedical researchers. The resulting code, Simbody, supports research in a variety of fields including neuromuscular, prosthetic, and biomolecular simulation, and related research such as biologically-inspired design and control of humanoid robots and avatars. Simbody is the dynamics engine behind OpenSim, a widely used biomechanics simulation application. This article reviews issues that arise uniquely in biomedical research, and reports on the architecture, theory, and computational methods Simbody uses to address them. By addressing these needs explicitly Simbody provides a better match to the needs of researchers than can be obtained by adaptation of mechanical engineering or gaming codes. Simbody is a community resource, free for any purpose. We encourage wide adoption and invite contributions to the code base at https://simtk.org/home/simbody.

OpenSim: a musculoskeletal modeling and simulation framework for in silico investigations and exchange

Movement science is driven by observation, but observation alone cannot elucidate principles of human and animal movement. Biomechanical modeling and computer simulation complement observations and inform experimental design. Biological models are complex and specialized software is required for building, validating, and studying them. Furthermore, common access is needed so that investigators can contribute models to a broader community and leverage past work. We are developing OpenSim, a freely available musculoskeletal modeling and simulation application and libraries specialized for these purposes, by providing: musculoskeletal modeling elements, such as biomechanical joints, muscle actuators, ligament forces, compliant contact, and controllers; and tools for fitting generic models to subject-specific data, performing inverse kinematics and forward dynamic simulations. OpenSim performs an array of physics-based analyses to delve into the behavior of musculoskeletal models by employing Simbody, an efficient and accurate multibody system dynamics code. Models are publicly available and are often reused for multiple investigations because they provide a rich set of behaviors that enables different lines of inquiry. This report will discuss one model developed to study walking and applied to gain deeper insights into muscle function in pathological gait and during running. We then illustrate how simulations can test fundamental hypotheses and focus the aims of in vivo experiments, with a postural stability platform and human model that provide a research environment for performing human posture experiments in silico. We encourage wide adoption of OpenSim for community exchange of biomechanical models and methods and welcome new contributors.

Muscle contributions to propulsion and support during running

Muscles actuate running by developing forces that propel the body forward while supporting the body's weight. To understand how muscles contribute to propulsion (i.e., forward acceleration of the mass center) and support (i.e., upward acceleration of the mass center) during running we developed a three-dimensional muscle-actuated simulation of the running gait cycle. The simulation is driven by 92 musculotendon actuators of the lower extremities and torso and includes the dynamics of arm motion. We analyzed the simulation to determine how each muscle contributed to the acceleration of the body mass center. During the early part of the stance phase, the quadriceps muscle group was the largest contributor to braking (i.e., backward acceleration of the mass center) and support. During the second half of the stance phase, the soleus and gastrocnemius muscles were the greatest contributors to propulsion and support. The arms did not contribute substantially to either propulsion or support, generating less than 1% of the peak mass center acceleration. However, the arms effectively counterbalanced the vertical angular momentum of the lower extremities. Our analysis reveals that the quadriceps and plantarflexors are the major contributors to acceleration of the body mass center during running.