An Electromyographically Driven Cervical Spine Model in OpenSim

A benchmark of muscle models to length changes great and small

Digital human body models are used to simulate injuries that occur as a result of vehicle collisions, vibration, sports, and falls. Given enough time the body's musculature can generate force, affect the body's movements, and change the risk of some injuries. The finite-element code LS-DYNA is often used to simulate the movements and injuries sustained by the digital human body models as a result of an accident. In this work, we evaluate the accuracy of the three muscle models in LS-DYNA (MAT_156, EHTM, and the VEXAT) when simulating a range of experiments performed on isolated muscle: force-length-velocity experiments on maximally and sub-maximally stimulated muscle, active-lengthening experiments, and vibration experiments. The force-length-velocity experiments are included because these conditions are typical of the muscle activity that precedes an accident, while the active-lengthening and vibration experiments mimic conditions that can cause injury. The three models perform similarly during the maximally and sub-maximally activated force-length-velocity experiments, but noticeably differ in response to the active-lengthening and vibration experiments. The VEXAT model is able to generate the enhanced forces of biological muscle during active lengthening, while both the MAT_156 and EHTM produce too little force. In response to vibration, the stiffness and damping of the VEXAT model closely follows the experimental data while the MAT_156 and EHTM models differ substantially. The accuracy of the VEXAT model comes from two additional mechanical structures that are missing in the MAT_156 and EHTM models: viscoelastic cross-bridges, and an active titin filament. To help others build on our work we have made our simulation code publicly available.

Neck stiffness and range of motion for young males and females

Well characterised mechanical response of the normal head-neck complex during passive motion is important to inform and verify physical surrogate and computational models of the human neck, and to inform normal baseline for clinical assessments. For 10 male and 10 female participants aged 20 to 29, the range of motion (ROM) of the neck about three anatomical axes was evaluated in active-seated, passive-lying and active-lying configurations, and the neck stiffness was evaluated in passive-lying. Electromyographic signals from the agonist muscles, normalised to maximum voluntary contractions, were used to provide feedback during passive motions. The effect of sex and configuration on ROM, and the effect of sex on linear estimates of stiffness in three regions of the moment-angle curve, were assessed with linear mixed models and generalised linear models. There were no differences in male and female ROM across all motion directions and configurations. Flexion and axial rotation ROM were configuration dependent. The passive-lying moment-angle relationship was typically non-linear, with higher stiffness (slope) closer to end of ROM. When normalising the passive moment-angle curve to active lying ROM, passive stiffness was sex dependent only for lateral bending region 1 and 2. Aggregate moment-angle corridors were similar for males and females in flexion and extension, but exhibited a higher degree of variation in applied moment for males in lateral bending and axial rotation. These data provide the passive response of the neck to low rate bending and axial rotation angular displacement, which may be useful for computational and surrogate modelling of the human neck.

Quantifying the Importance of Active Muscle Repositioning a Finite Element Neck Model in Flexion Using Kinematic, Kinetic, and Tissue-Level Responses

PURPOSE

Non-neutral neck positions are important initial conditions in impact scenarios, associated with a higher incidence of injury. Repositioning in finite element (FE) neck models is often achieved by applying external boundary conditions (BCs) to the head while constraining the first thoracic vertebra (T1). However, in vivo, neck muscles contract to achieve a desired head and neck position generating initial loads and deformations in the tissues. In the present study, a new muscle-based repositioning method was compared to traditional applied BCs using a contemporary FE neck model for forward head flexion of 30°.

METHODS

For the BC method, an external moment (2.6 Nm) was applied to the head with T1 fixed, while for the muscle-based method, the flexors and extensors were co-contracted under gravity loading to achieve the target flexion.

RESULTS

The kinematic response from muscle contraction was within 10% of the in vivo experimental data, while the BC method differed by 18%. The intervertebral disc forces from muscle contraction were agreeable with the literature (167 N compression, 12 N shear), while the BC methodology underpredicted the disc forces owing to the lack of spine compression. Correspondingly, the strains in the annulus fibrosus increased by an average of 60% across all levels due to muscle contraction compared to BC method.

CONCLUSION

The muscle repositioning method enhanced the kinetic response and subsequently led to differences in tissue-level responses compared to the conventional BC method. The improved kinematics and kinetics quantify the importance of repositioning FE neck models using active muscles to achieve non-neutral neck positions.

Cervical Spine Motion Requirements From Night Vision Goggles May Play a Greater Role in Chronic Neck Pain than Helmet Mass Properties

BACKGROUND

Chronic Neck Pain (CNP) among rotary-wing aircrew is thought to stem from night vision goggles (NVG) and counterweight (CW) systems which displace the centre of mass of the head. This investigation aimed to quantify the loads acting on the neck as a function of movement magnitude (MM), helmet conditions, and movement axes in rapid movements.

METHODS

Cervical spine kinematics during rapid head repositioning tasks for flexion-extension (FE) and axial rotation (AR) movements were measured from 15 males and 15 females. Participants moved in either a 35° (Near MM) or 70° arc (Far MM), while donning a helmet, helmet with NVG, helmet with NVG and a typical CW, and a CW Liner (CWL). Measured EMG from three muscles bilaterally and used to drive a biomechanical model to quantify the compression and shear acting at the C5-C6 joint.

RESULTS

In AR, the NVGs were associated with the largest compression magnitudes, 252 (24) N. CW conditions decreased the maximum compression to 249 (53) N. For FE, the compression was 340 N for the Far MM trials and 246 N for Near MMs. Changing the helmet configuration only modestly influenced these magnitudes in FE.

CONCLUSION

Every 30° of MM increased compression by 57 to 105 N. The reduction of the moment of inertia by 16% in the CWL did not reduce reaction forces. Joint loads scaled proportionately with head-supported weight by a factor of 2.05. The magnitudes of loads suggest a cumulative loading pathway for CNP development.

Influence of different calibration methods on surface electromyography-informed musculoskeletal models with few input signals

BACKGROUND

Although model personalization is critical when assessing individuals with morphological or neurological abnormalities, or even non-disabled subjects, its translation into routine clinical settings is hampered by the cumbersomeness of experimental data acquisition and lack of resources, which are linked to high costs and long processing pipelines. Quantifying the impact of neglecting subject-specific information in simulations that aim to estimate muscle forces with surface electromyography informed modeling approaches, can address their potential in relevant clinical questions. The present study investigates how different methods to fine-tune subject-specific neuromuscular parameters, reducing the number of electromyography input data, could affect the estimation of the unmeasured excitations and the musculotendon forces.

METHODS

Three-dimensional motion analysis was performed on 8 non-disabled adult subjects and 13 electromyographic signals captured. Four neuromusculoskeletal models were created for 8 participants: a reference model driven by a large set of sEMG signals; two models informed by four electromyographic signals but calibrated in different fashions; a model based on static optimization.

FINDINGS

The electromyography-informed models better predicted experimental excitations, including the unmeasured ones. The model based on static optimization obtained less reliable predictions of the experimental data. When comparing the different reduced models, no major differences were observed, suggesting that the less complex model may suffice for predicting muscle forces with a small set of input in clinical gait analysis tasks.

INTERPRETATION

Quantitative model performance evaluation in different conditions provides an objective indication of which method yields the most accurate prediction when a small set of electromyographic recordings is available.

Head supported mass, moment of inertia, neck loads and stability: A simulation study

Occupations or activities where donning head-supported mass (HSM) is commonplace put operators at an elevated risk of chronic neck pain. Yet, there is no consensus about what features of HSM influence the relative contributions to neck loads. Therefore, we tested four hypotheses that could increase neck loads: (i) HSM increases gravitational moments; (ii) more muscle activation is required to stabilize the head with HSM; (iii) the position of the HSM centre of mass (COM) induces gravitational moments; and (iv) the added moment of inertia (MOI) from HSM increases neck loads during head repositioning tasks. We performed a sensitivity analysis on the C5-C6 compression evaluated from a 24-degree freedom cervical spine model in OpenSim for static and dynamic movement trials. For static trials, we varied the magnitude of HSM, the position of its COM, and developed a novel stability constraint for static optimization. In dynamic trials, we varied HSM and the three principle MOIs. HSM magnitude and compression were linearly related to one another for both static and dynamic trials, with amplification factors varying between 1.9 and 3.9. Similar relationships were found for the COM position, although the relationship between C5-C6 peak compression and MOI in dynamic trials was generally nonlinear. This sensitivity analysis uncovered evidence in favour of hypotheses (i), (ii) and (iii). However, the model's prediction of C5-C6 compression was not overly sensitive to the magnitude of MOI. Therefore, the HSM mass properties may be more influential on neck compression than MOI properties, even during dynamic tasks.

[Mathematical modeling using finite element analysis in forensic medical examination]

The purpose of the work is to develop methods of mathematical modeling using finite element analysis in forensic medical examination. The stages of the methodology for solving problems of deformable body mechanics in forensic medicine are considered, which allows to reliably establish the possibility of formation and morphology of damage under specific conditions and circumstances, to focus the researcher's attention on problem points when creating and evaluating the model. The use of simplified models of the human body makes the expert's conclusion more reasonable, which increases the confidence of law enforcement agencies in the activities of the forensic medical expert service and allows for a new look at solving the problems of forensic medicine and forensic medical examination.

Posture and Helmet Configuration Effects on Joint Reaction Loads in the Middle Cervical Spine

INTRODUCTION: Between 43 and 97% of helicopter pilots in the Canadian Armed Forces report neck pain. Potential contributing factors include the weight of their helmet, night vision goggles (NVG), and counterweight (CW) combined with deviated neck postures. Therefore, the purpose of this investigation was to quantify changes in neck loads associated with posture, helmet, NVG, and CW.METHODS: Eight male subjects volunteered. They undertook one of five deviated neck postures (flexion, extension, lateral bending, axial rotation) times four configurations (no helmet, helmet only, helmet and NVG, and helmet, NVG, and CW). 3D kinematics and EMG from 10 muscles (5 bilaterally) drove a 3D inverse dynamics, EMG-driven model of the cervical spine which calculated joint compression and shear at C5-C6.RESULTS: The compression in the neutral posture was 116.5 (5.7) N, which increased to 143.7 (11.4) N due to a 12.7 N helmet. NVGs, weighing 7.9 N, also generated this disproportionate increase, where the compression was 164.2 (3.7) N. In flexion or extension, the compression increased with increasing head-supported mass, with a maximum of 315.8 (67.5) N with the CW in flexion. Anteroposterior shear was highest in the lateral bending [34.0 (6.2) N] condition, but was generally low (< 30 N). Mediolateral shear was less than 5 N for all conditions.DISCUSSION: Repositioning the center of gravity of the helmet with either NVGs or CW resulted in posture-specific changes to loading. Posture demonstrated a greater potential to reposition the head segment's center of gravity compared to the helmet design. Therefore, helmet designs which consider repositioning the center of gravity may reduce loads in one posture, but likely exacerbate loading in other postures.Barrett JM, McKinnon CD, Dickerson CR, Laing AC, Callaghan JP. Posture and helmet configuration effects on joint reaction loads in the middle cervical spine. Aerosp Med Hum Perform. 2022; 93(5):458-466.

Predicting Cervical Spine Compression and Shear in Helicopter Helmeted Conditions Using Artificial Neural Networks

OCCUPATIONAL APPLICATIONSMilitary helicopter pilots around the globe are at high risk of neck pain related to their use of helmet-mounted night vision goggles. Unfortunately, it is difficult to design alternative helmet configurations that reduce the biomechanical exposures on the cervical spine during flight because the time and resource costs associated with assessing these exposures in vivo are prohibitive. Instead, we developed artificial neural networks (ANNs) to predict cervical spine compression and shear given head-trunk kinematics and joint moments in the lower neck, data readily available from digital human models. The ANNs detected differences in cervical spine compression and anteroposterior shear between helmet configuration conditions during flight-relevant head movement, consistent with results from a detailed model based on in vivo electromyographic data. These ANNs may be useful in helping to prevent neck pain related to military helicopter flight by facilitating virtual biomechanical assessment of helmet configurations upstream in the design process.