Implementation of controlling strategy in a biomechanical lower limb model with active muscles for coupling multibody dynamics and finite element analysis

Computational biomechanics for human body modeling has generally been categorized into two separated domains: finite element analysis and multibody dynamics. Combining the advantages of both domains is necessary when tissue stress and physical body motion are both of interest. However, the method for this topic is still in exploration. The aim of this study is to implement unique controlling strategies in finite element model for simultaneously simulating musculoskeletal body dynamics and in vivo stress inside human tissues. A finite element lower limb model with 3D active muscles was selected for the implementation of controlling strategies, which was further validated against in-vivo human motion experiments. A unique feedback control strategy that couples together a basic Proportion-Integration-Differentiation (PID) controller and generic active signals from Computed Muscle Control (CMC) method of the musculoskeletal model or normalized EMG singles was proposed and applied in the present model. The results show that the new proposed controlling strategy show a good correlation with experimental test data of the normal gait considering joint kinematics, while stress distribution of local lower limb tissue can be also detected in real-time with lower limb motion. In summary, the present work is the first step for the application of active controlling strategy in the finite element model for concurrent simulation of both body dynamics and tissue stress. In the future, the present method can be further developed to apply it in various fields for human biomechanical analysis to monitor local stress and strain distribution by simultaneously simulating human locomotion.     

A computationally efficient strategy to estimate muscle forces in a finite element musculoskeletal model of the lower limb

Concurrent multiscale simulation strategies are required in computational biomechanics to study the interdependence between body scales. However, detailed finite element models rarely include muscle recruitment due to the computational burden of both the finite element method and the optimization strategies widely used to estimate muscle forces. The aim of this study was twofold: first, to develop a computationally efficient muscle force prediction strategy based on proportional-integral-derivative (PID) controllers to track gait and chair rise experimental joint motion with a finite element musculoskeletal model of the lower limb, including a deformable knee representation with 12 degrees of freedom; and, second, to demonstrate that the inclusion of joint-level deformability affects muscle force estimation by using two different knee models and comparing muscle forces between the two solutions. The PID control strategy tracked experimental hip, knee, and ankle flexion/extension with root mean square errors below 1°, and estimated muscle, contact and ligament forces in good agreement with previous results and electromyography signals. Differences up to 11% and 20% in the vasti and biceps femoris forces, respectively, were observed between the two knee models, which might be attributed to a combination of differing joint contact geometry, ligament behavior, joint kinematics, and muscle moment arms. The tracking strategy developed in this study addressed the inevitable tradeoff between computational cost and model detail in musculoskeletal simulations and can be used with finite element musculoskeletal models to efficiently estimate the interdependence between muscle forces and tissue deformation.     

Foot arch deformation and plantar fascia loading during running with rearfoot strike and forefoot strike: A dynamic finite element analysis

Forefoot strike becomes popular among runners because it facilitates better impact attenuation. However, forefoot strike may overload the plantar fascia and impose risk of plantar fasciitis. This study aimed to examine and compare the foot arch deformation and plantar fascia tension between different foot strike techniques in running using a computational modelling approach. A three-dimensional finite element foot model was reconstructed from the MRI of a healthy runner. The foot model included twenty bones, bulk soft tissue, ligaments, tendons, and plantar fascia. The time-series data of segmental kinematics, foot muscle force, and ankle joint reaction force were derived from a musculoskeletal model of the same participant based on the motion capture analysis and input as the boundary conditions for the finite element analysis. Rearfoot strike and forefoot strike running were simulated using a dynamic explicit solver. The results showed that, compared to rearfoot strike, forefoot strike reduced the foot arch height by 9.12% and increased the medial longitudinal arch angle by 2.06%. Forefoot strike also increased the plantar connective tissues stress by 18.28–200.11% and increased the plantar fascia tensile force by 18.71–109.10%. Although it is currently difficult to estimate the threshold value of stress or force that results in injury, forefoot strike runners appeared to be more vulnerable to plantar fasciitis.     

A lower extremity model for muscle-driven simulation of activity using explicit finite element modeling

A key strength of computational modeling is that it can provide estimates of muscle, ligament, and joint loads, stresses, and strains through non-invasive means. However, simulations that can predict the forces in the muscles during activity while maintaining sufficient complexity to realistically represent the muscles and joint structures can be computationally challenging. For this reason, the current state of the art is to apply separate rigid-body dynamic and finite-element (FE) analyses in series. However, the use of two or more disconnected models often fails to capture key interactions between the joint-level and whole-body scales. Single framework MSFE models have the potential to overcome the limitations associated with disconnected models in series. The objectives of the current study were to create a multi-scale FE model of the human lower extremity that combines optimization, dynamic muscle modeling, and structural FE analysis in a single framework and to apply this framework to evaluate the mechanics of healthy knee specimens during two activities. Two subject-specific FE models (Model 1, Model 2) of the lower extremity were developed in ABAQUS/Explicit including detailed representations of the muscles. Muscle forces, knee joint loading, and articular contact were calculated for two activities using an inverse dynamics approach and static optimization. Quadriceps muscle forces peaked at the onset of chair rise (2174 N, 1962 N) and in early stance phase (510 N, 525 N), while gait saw peak forces in the hamstrings (851 N, 868 N) in midstance. Joint forces were similar in magnitude to available telemetric patient data. This study demonstrates the feasibility of detailed quasi-static, muscle-driven simulations in an FE framework.     

Estimation of in vivo inter-vertebral loading during motion using fluoroscopic and magnetic resonance image informed finite element models

Finite element (FE) models driven by medical image data can be used to estimate subject-specific spinal biomechanics. This study aimed to combine magnetic resonance (MR) imaging and quantitative fluoroscopy (QF) in subject-specific FE models of upright standing, flexion and extension. Supine MR images of the lumbar spine were acquired from healthy participants using a 0.5 T MR scanner. Nine 3D quasi-static linear FE models of L3 to L5 were created with an elastic nucleus and orthotropic annulus. QF data was acquired from the same participants who performed trunk flexion to 60° and trunk extension to 20°. The displacements and rotations of the vertebrae were calculated and applied to the FE model. Stresses were averaged across the nucleus region and transformed to the disc co-ordinate system (S1 = mediolateral, S2 = anteroposterior, S3 = axial). In upright standing S3 was predicted to be −0.7 ± 0.6 MPa (L3L4) and −0.6 ± 0.5 MPa (L4L5). S3 increased to −2.0 ± 1.3 MPa (L3L4) and −1.2 ± 0.6 MPa (L4L5) in full flexion and to −1.1 ± 0.8 MPa (L3L4) and −0.7 ± 0.5 MPa (L4L5) in full extension. S1 and S2 followed similar patterns; shear was small apart from S23. Disc stresses correlated to disc orientation and wedging. The results demonstrate that MR and QF data can be combined in a participant-specific FE model to investigate spinal biomechanics in vivo and that predicted stresses are within ranges reported in the literature.     

Construction of a risk model through the fusion of experimental data and finite element modeling: Application to car crash-induced TBI

This article introduces a new approach for the construction of a risk model for the prediction of Traumatic Brain Injury (TBI) as a result of a car crash. The probability of TBI is assessed through the fusion of an experiment-based logistic regression risk model and a finite element (FE) simulation-based risk model. The proposed approach uses a multilevel framework which includes FE simulations of vehicle crashes with dummy and FE simulations of the human brain. The loading conditions derived from the crash simulations are transferred to the brain model thus allowing the calculation of injury metrics such as the Cumulative Strain Damage Measure (CSDM). The framework is used to propagate uncertainties and obtain probabilities of TBI based on the CSDM injury metric. The risk model from FE simulations is constructed from a support vector machine classifier, adaptive sampling, and Monte-Carlo simulations. An approach to compute the total probability of TBI, which combines the FE-based risk assessment as well as the risk prediction from the experiment-based logistic regression model is proposed. In contrast to previous published work, the proposed methodology includes the uncertainty of explicit parameters such as impact conditions (e.g., velocity, impact angle), and material properties of the brain model. This risk model can provide, for instance, the probability of TBI for a given assumed crash impact velocity.     

The development of an EMG-assisted model to assess spine loading during whole-body free-dynamic lifting

Low back disorders (LBDs) are the most common and costly occupationally-related compensable conditions facing employers today. Over the years several biomechanical assessment models have been developed that intended to assess the load profile imposed upon the spine during lifting and, thus, intended to facilitate the control of LBD risk in the workplace. Many of these biomechanical models have evolved based upon assumptions about how the trunk musculature respond to loads imposed upon the body during lifting. However, few of these models have been able to accurately predict the co-contraction of the trunk musculature which has been shown to have a major influence on the development of spinal loads. Thus, our understanding of how the spine is loaded under realistic dynamic lifting conditions has been deficient. A biologically-assisted or EMG-assisted model has been developed in our laboratory over the past 15 years which endeavours to overcome these traditional problems. The model has been assessed in the sagittal, coronal, and torsional planes of the body. The model development and performance will be reviewed as well as the benefits for controlling occupationally-related LBDs.     

Finite element model of the human neck during omni-directional impacts. Part II: relation between cervical curvature and risk of injury

A detailed 3D FE model of the human neck was used to assess a possible relationship between risk of injury and cervical spine curvature for various impacts. A FE model was previously developed, representing the head and neck of a 50th percentile human with a normal lordotic curvature. The model behaviour was omni-directionally validated for various impacts using published results. For the present study, the model was deformed in order to obtain a straight and a kyphotic curvature, and for each geometry, rear-end, frontal, lateral and oblique impact were simulated. Although results showed similar kinematic patterns, significant differences were found in the distribution and peak values of ligament elongations, forces and moments along the cervical spine for the three configurations. It was concluded that the variability observed on the curvature of the human cervical spine may have a significant influence both on the behaviour and on the risk of injury of the neck during impact.     

A finite element study relating to the rapid filling phase of the human ventricles

During the rapid diastolic filling phase at rest, the ventricles of the human heart double approximately in volume. In order to investigate whether the ventricular filling pressures measured under physiological conditions can give rise to such an extensive augmentation in ventricular volumes, a finite element model of the human right and left ventricles has been developed, taking into account the nonlinear mechanical behavior and effective compressibility of the myocardial tissue. The results were compared with the filling phase of the human left ventricle as extrapolated from measurements documented in the literature. We arrived at the conclusion that the ventricular pressures measured during the rapid filling phase cannot be the sole cause of the rise of the observed ventricular volumes. We rather advocate the assumption that further dilating mechanisms might be part of ventricular activity thus heralding a multiple function of the ventricular muscle body. A further result indicates that under normal conditions the influence of the viscoelasticity of the tissue should not be disregarded in ventricular mechanics.     

Validation of a full body finite element model (THUMS) for running-type impacts to the lower extremity

The purpose of this study was to determine whether modifying an existing, highly biofidelic full body finite element model [total human model for safety (THUMS)] would produce valid amplitude and temporal shock wave characteristics as it travels proximally through the lower extremity. Modifying an existing model may be more feasible than developing a new model, in terms of cost, labour and expertise. The THUMS shoe was modified to more closely simulate the material properties of a heel pad. Relative errors in force and acceleration data from experimental human pendulum impacts and simulated THUMS impacts were 22% and 54%, respectively, across the time history studied. The THUMS peak acceleration was attenuated by 57.5% and took 19.7 ms to travel proximally along the lower extremity. Although refinements may be necessary to improve force and acceleration timing, the modified THUMS represented, to a certain extent, shock wave propagation and attenuation demonstrated by living humans under controlled impact conditions.     

Using the finite element method to model the biomechanics of the asymmetric mandible before,during and after skeletal correction by distraction osteogenesis

An approach was developed to evaluate the load transfer mechanism in the temporomandibular joint (TMJ) area before, during and after mandibular ramus elongation by distraction osteogenesis (DO). In a concerted approach using computer tomography, magnetic resonance imaging (MRI), and finite element analysis, three-dimensional numerical models based on a young male patient, with a dento-facial deformity were generated. The magnitude and direction of the muscle forces acting on the mandible were assessed using both values derived from the muscles volume and cross-section as retrieved from the MRI-scan data-sets and taken from the literature. The resistance of the soft tissue envelope towards elongation during the DO-phase was also included. The finite element analyses showed that before skeletal correction by DO the load transfer was asymmetrical with high peak stresses in the affected joint. Following ramus elongation a more symmetrical loading in TMJs was predicted. The reaction forces in the TMJs during DO were low.     

A centric/non-centric impact protocol and finite element model methodology for the evaluation of American football helmets to evaluate risk of concussion

American football reports high incidences of head injuries, in particular, concussion. Research has described concussion as primarily a rotation dominant injury affecting the diffuse areas of brain tissue. Current standards do not measure how helmets manage rotational acceleration or how acceleration loading curves influence brain deformation from an impact and thus are missing important information in terms of how concussions occur. The purpose of this study was to investigate a proposed three-dimensional impact protocol for use in evaluating football helmets. The dynamic responses resulting from centric and non-centric impact conditions were examined to ascertain the influence they have on brain deformations in different functional regions of the brain that are linked to concussive symptoms. A centric and non-centric protocol was used to impact an American football helmet; the resulting dynamic response data was used in conjunction with a three-dimensional finite element analysis of the human brain to calculate brain tissue deformation. The direction of impact created unique loading conditions, resulting in peaks in different regions of the brain associated with concussive symptoms. The linear and rotational accelerations were not predictive of the brain deformation metrics used in this study. In conclusion, the test protocol used in this study revealed that impact conditions influences the region of loading in functional regions of brain tissue that are associated with the symptoms of concussion. The protocol also demonstrated that using brain deformation metrics may be more appropriate when evaluating risk of concussion than using dynamic response data alone.     

Effects of lumbo-pelvic rhythm on trunk muscle forces and disc loads during forward flexion: A combined musculoskeletal and finite element simulation study

Previous in-vivo studies suggest that the ratio of total lumbar rotation over pelvic rotation (lumbo-pelvic rhythm) during trunk sagittal movement is essential to evaluate spinal loads and discriminate between low back pain and asymptomatic population. Similarly, there is also evidence that the lumbo-pelvic rhythm is key for evaluation of realistic muscle and joint reaction forces and moments predicted by various computational musculoskeletal models. This study investigated the effects of three lumbo-pelvic rhythms defined based on in-vivo measurements on the spinal response during moderate forward flexion (60°) using a combined approach of musculoskeletal modeling of the upper body and finite element model of the lumbosacral spine. The muscle forces and joint loads predicted by the musculoskeletal model, together with the gravitational forces, were applied to the finite element model to compute the disc force and moment, intradiscal pressure, annular fibers strain, and load-sharing. The results revealed that a rhythm with high pelvic rotation and low lumbar flexion involves more global muscles and increases the role of the disc in resisting spinal loads, while its counterpart, with low pelvic rotation, recruits more local muscles and engages the ligaments to lower the disc loads. On the other hand, a normal rhythm that has balanced pelvic and lumbar rotations yields almost equal disc and ligament load-sharing and results in more balanced synergy between global and local muscles. The lumbo-pelvic rhythm has less effect on the intradiscal pressure and annular fibers strain. This work demonstrated that the spinal response during forward flexion is highly dependent on the lumbo-pelvic rhythm. It is therefore, essential to adapt this parameter instead of using the default values in musculoskeletal models for accurate prediction of muscle forces and joint reaction forces and moments. The findings provided by this work are expected to improve knowledge of spinal response during forward flexion, and are clinically relevant towards low back pain treatment and disc injury prevention.