Effect of Subject-Specific Vertebral Position and Head and Neck Size on Calculation of Spine Musculoskeletal Moments

Inverse kinematics in cervical spine models: Effects of scaling and model degrees of freedom for extension and flexion movements

Intervertebral kinematics can affect model-predicted loads and strains in the spine; therefore knowledge of expected vertebral kinematics error is important for understanding the limitations of model predictions. This study addressed how different kinematic models of the neck affect the prediction of intervertebral kinematics from markers on the head and trunk. Eight subjects executed head and neck extension-flexion motion with simultaneous motion capture and biplanar dynamic stereo-radiography (DSX) of vertebrae C1-C7. A generic head and neck model in OpenSim was scaled by marker data, and three versions of the model were used with an inverse kinematics solver. The models differed according to the number of independent degrees of freedom (DOF) between the head and trunk: 3 rotational DOF with constraints defining intervertebral kinematics as a function of overall head-trunk motion; 24DOF with 3 independent rotational DOF at each level, skull-T1; 48DOF with 3 rotational and 3 translational DOF at each level. Marker tracking error was lower for scaled models compared to generic models and decreased as model DOF increased. The largest mean absolute error (MAE) was found in extension-flexion angle and anterior-posterior translation at C1-C2, and superior-inferior translation at C2-C3. Model scaling and complexity did not have a statistically significant effect on most error metrics when corrected for multiple comparisons, but ranges of motion were significantly different from DSX in some cases. This study evaluated model kinematics in comparison to gold standard radiographic data and provides important information about intervertebral kinematics error that are foundational to model validity.

An Electromyographically Driven Cervical Spine Model in OpenSim

Relatively few biomechanical models exist aimed at quantifying the mechanical risk factors associated with neck pain. In addition, there is a need to validate spinal-rhythm techniques for inverse dynamics spine models. Therefore, the present investigation was 3-fold: (1) the development of a cervical spine model in OpenSim, (2) a test of a novel spinal-rhythm technique based on minimizing the potential energy in the passive tissues, and (3) comparison of an electromyographically driven approach to estimating compression and shear to other cervical spine models. The authors developed ligament force-deflection and intervertebral joint moment-angle curves from published data. The 218 Hill-type muscle elements, representing 58 muscles, were included and their passive forces validated against in vivo data. Our novel spinal-rhythm technique, based on minimizing the potential energy in the passive tissues, disproportionately assigned motion to the upper cervical spine that was not physiological. Finally, using kinematics and electromyography collected from 8 healthy male volunteers, the authors calculated the compression at C7-T1 as a function of the head-trunk Euler angles. Differences from other models varied from 25.5 to 368.1 N. These differences in forces may result in differences in model geometry, passive components, number of degrees of freedom, or objective functions.

Cervical Spine Musculotendon Lengths When Reading a Tablet in Three Seated Positions

A popular posture for using wireless technology is reclined sitting, with the trunk rotated posteriorly to the hips. This position decreases the head's gravitational moment; however, the head angle relative to the trunk is similar to that of upright sitting when using a tablet in the lap. This study compared cervical extensor musculotendon length changes from neutral among 3 common sitting postures and maximum neck flexion while using a tablet. Twenty-one participants had radiographs taken in neutral, full-flexion, and upright, semireclined, and reclined postures with a tablet in their lap. A biomechanical model was used to calculate subject-specific normalized musculotendon lengths for 27 cervical musculotendon segments. The lower cervical spine was more flexed during reclined sitting, but the skull was more flexed during upright sitting. Normalized musculotendon length increased in the reclined compared with an upright sitting position for the C4-C6/7 (deep) and C2-C6/7 (superficial) multifidi, semispinalis cervicis (C2-C7), and splenius capitis (Skull-C7). The suboccipital (R2 = .19-.71) and semispinalis capitis segment length changes were significantly correlated with the Skull-C1 angle (0.24-0.51). A semireclined reading position may be an ideal sitting posture to reduce the head's gravitational moment arm without overstretching the assessed muscles.

Neck musculoskeletal model generation through anthropometric scaling

A new methodology was developed to quickly generate whole body models with detailed neck musculoskeletal architecture that are properly scaled in terms of anthropometry and muscle strength. This method was implemented in an anthropometric model generation software that allows users to interactively generate any new male or female musculoskeletal models with adjustment of anthropometric parameters (such as height, weight, neck circumference, and neck length) without the need of subject-specific motion capture or medical images. 50^th percentile male and female models were developed based on the 2012 US Army Anthropometric Survey (ANSUR II) database and optimized with a novel bilevel optimization method to have strengths comparable to experimentally measured values in the literature. Other percentile models (ranging from the 1^st to 99^th percentile) were generated based on anthropometric scaling of the 50^th percentile models and compared. The resultant models are reasonably accurate in terms of both musculoskeletal geometry and neck strength, demonstrating the effectiveness of the developed methodology for interactive neck model generation with anthropometric scaling.