Neck muscle load distribution in lateral, frontal, and rear-end impacts: a three-dimensional finite element analysis.

STUDY DESIGN: A finite element (FE) model of the human neck was used to study the distribution of neck muscle loads during multidirectional impacts. The computed load distributions were compared to experimental electromyography (EMG) recordings. OBJECTIVE: To quantify passive muscle loads in nonactive cervical muscles during impacts of varying direction and energy, using a three-dimensional (3D) continuum FE muscle model. SUMMARY OF BACKGROUND DATA: Experimental and numerical studies have confirmed the importance of muscles in the impact response of the neck. Although EMG has been used to measure the relative activity levels in neck muscles during impact tests, this technique has not been able to measure all neck muscles and cannot directly quantify the force distribution between the muscles. A numerical model can give additional insight into muscle loading during impact. METHODS: An FE model with solid element musculature was used to simulate frontal, lateral, and rear-end vehicle impacts at 4 peak accelerations. The peak cross-sectional forces, internal energies, and effective strains were calculated for each muscle and impact configuration. The computed load distribution was compared with experimental EMG data. RESULTS: The load distribution in the cervical muscles varied with load direction. Peak sectional forces, internal energies, and strains increased in most muscles with increasing impact acceleration. The dominant muscles identified by the model for each direction were splenius capitis, levator scapulae, and sternocleidomastoid in lateral impacts, splenius capitis, and trapezoid in frontal impacts, and sternocleidomastoid, rectus capitis posterior minor, and hyoids in rear-end impacts. This corresponded with the most active muscles identified by EMG recordings, although within these muscles the distribution of forces and EMG levels were not the same. CONCLUSION: The passive muscle forces, strains, and energies computed using a continuum FE model of the cervical musculature distinguished between impact directions and peak accelerations, and on the basis of prior studies, isolated the most important muscles for each direction.

How does a three-dimensional continuum muscle model affect the kinematics and muscle strains of a finite element neck model compared to a discrete muscle model in rear-end, frontal, and lateral impacts.

STUDY DESIGN: A finite element (FE) model of the human neck with incorporated continuum or discrete muscles was used to simulate experimental impacts in rear, frontal, and lateral directions. OBJECTIVE: The aim of this study was to determine how a continuum muscle model influences the impact behavior of a FE human neck model compared with a discrete muscle model. SUMMARY OF BACKGROUND DATA: Most FE neck models used for impact analysis today include a spring element musculature and are limited to discrete geometries and nodal output results. A solid-element muscle model was thought to improve the behavior of the model by adding properties such as tissue inertia and compressive stiffness and by improving the geometry. It would also predict the strain distribution within the continuum elements. METHODS: A passive continuum muscle model with nonlinear viscoelastic materials was incorporated into the KTH neck model together with active spring muscles and used in impact simulations. The resulting head and vertebral kinematics was compared with the results from a discrete muscle model as well as volunteer corridors. The muscle strain prediction was compared between the 2 muscle models. RESULTS: The head and vertebral kinematics were within the volunteer corridors for both models when activated. The continuum model behaved more stiffly than the discrete model and needed less active force to fit the experimental results. The largest difference was seen in the rear impact. The strain predicted by the continuum model was lower than for the discrete model. CONCLUSION: The continuum muscle model stiffened the response of the KTH neck model compared with a discrete model, and the strain prediction in the muscles was improved.

Electromyography of superficial and deep neck muscles during isometric, voluntary, and reflex contractions.

Increasingly complex models of the neck neuromusculature need detailed muscle and kinematic data for proper validation. The goal of this study was to measure the electromyographic activity of superficial and deep neck muscles during tasks involving isometric, voluntary, and reflexively evoked contractions of the neck muscles. Three male subjects (28-41 years) had electromyographic (EMG) fine wires inserted into the left sternocleidomastoid, levator scapulae, trapezius, splenius capitis, semispinalis capitis, semispinalis cervicis, and multifidus muscles. Surface electrodes were placed over the left sternohyoid muscle. Subjects then performed: (i) maximal voluntary contractions (MVCs) in the eight directions (45 deg intervals) from the neutral posture; (ii) 50 N isometric contractions with a slow sweep of the force direction through 720 deg; (iii) voluntary oscillatory head movements in flexion and extension; and (iv) initially relaxed reflex muscle activations to a forward acceleration while seated on a sled. Isometric contractions were performed against an overhead load cell and movement dynamics were measured using six-axis accelerometry on the head and torso. In all three subjects, the two anterior neck muscles had similar preferred activation directions and acted synergistically in both dynamic tasks. With the exception of splenius capitis, the posterior and posterolateral neck muscles also showed consistent activation directions and acted synergistically during the voluntary motions, but not during the sled perturbations. These findings suggest that the common numerical-modeling assumption that all anterior muscles act synergistically as flexors is reasonable, but that the related assumption that all posterior muscles act synergistically as extensors is not. Despite the small number of subjects, the data presented here can be used to inform and validate a neck model at three levels of increasing neuromuscular-kinematic complexity: muscles generating forces with no movement, muscles generating forces and causing movement, and muscles generating forces in response to induced movement. These increasingly complex data sets will allow researchers to incrementally tune their neck models' muscle geometry, physiology, and feedforward/feedback neuromechanics.