Experimental Characterization of the Anatomical Structures of the Lumbar Spine Under Dynamic Sagittal Bending.

Underbody blast (UBB) events transmit high-rate vertical loads through the seated occupant’s lumbar spine and have a high probability of inducing severe injury. While previous studies have characterized the lumbar spine under quasi-static loading, additional work should focus on the complex kinetic and kinematic response under high loading rates. To discern the biomechanical influence of the lumbar spine’s anatomical structures during dynamic loading, the axial force, flexion-extension moments and range of motion for lumbar motion segments (n=18) were measured during different states of progressive dissection. Pre-compression was applied using a static mass while dynamic bending was applied using an offset drop mass. Dynamic loading resulted in peak axial loads of 4,224±133 N, while maximum peak extension and flexion moments were 19.6±12.5 and -44.8±8.6 Nm in the pre-dissected state, respectively. Upon dissection, transection of the interspinous ligament, ligamentum flavum and facet capsules resulted in significantly larger flexion angles, while the removal of the posterior elements increased the total peak angular displacement in extension from 3.3±1.5 to 5.0±1.7 degrees (p=0.002). This study provides insight on the contribution of individual anatomical components on overall lumbar response under high-rate loading, as well as validation data for numerical models.

Automated Measurement Technique for the Determination of Regional Skull and Scalp Constituent Thickness.

The human skull is a multi-layered composite system critical in protecting the brain during head impact. Head impact studies investigating skull injury thresholds have suggested that the skull and scalp thickness affect the risk of fracture. Therefore, accurately determining the dimensions of skull-scalp constituents is a necessary step in attributing the contribution to response, failure mechanisms and in developing high fidelity human models. However, prior methods to collect these data include physical measurements of biopsies and manual segmentation in X-ray images. These methods are invasive and impractical for clinical applications, or insufficient to characterize the regional variance in the skull-scalp constituents for a full mechanical strength characterization. The newly developed methods in this study describe an automated, regional, and objective-based measurement technique to characterize the average thickness and variance in skull and scalp constituents using quantitative computed tomography (QCT). The developed approach was successfully employed on 7 specimens at 5 anatomically defined locations. Results report the thicknesses for each layer, with the layer of greatest variation being the trabecular bone (diploë) having a standard deviation of 35.6% of its mean thickness. These results will be used to define skull morphology for modeling relative impact injury risk that will be experimentally validated.

Material Parameter Determination of an L4-L5 Motion Segment Finite Element Model Under High Loading Rates.

Underbody blast (UBB) events impart vertical loads through a victim’s lumbar spine, resulting in fracture, paralysis, and disc rupture. Validated biofidelic lumbar models allow characterization of injury mechanisms and development of personal protective equipment. Previous studies have focused on lumbar mechanics under quasi-static loading. However, it is unclear how the role and response of individual spinal components of the lumbar spine change under dynamic loading. The present study leverages high-rate impacts of progressively dissected two-vertebra lumbar motion segments and Split-Hopkinson pressure bar tissue characterization to identify and validate material properties of a high-fidelity lumbar spine finite element model for UBB. The annulus fibrosus was modeled as a fiber-reinforced Mooney-Rivlin material, while ligaments were represented by nonlinear spring elements. Optimization and evaluation of material parameters was achieved by minimizing the root-mean-square (RMS) of compressive displacement and sagittal rotation for selected experimental conditions. Applying dynamic based material models and parameters resulted in a 0.42% difference between predicted and experiment axial compression during impact loading. This dynamically optimized lumbar model is suited for cross validation against whole-lumbar loading scenarios, and prediction of injury during UBB and other dynamic events.

Response of thoracolumbar vertebral bodies to high rate compressive loading - biomed 2013.

Underbody blast (UBB) events created by improvised explosive devices are threats to warfighter survivability. High intensity blast waves emitted from these devices transfer large forces through vehicle structures to occupants, often resulting in injuries including debilitating spinal fractures. The vertical loading vector through the spine generates significant compressive forces at high strain rates. To better understand injury mechanisms and ultimately better protect vehicle occupants against UBB attacks, high-fidelity computational models are being developed to predict the human response to dynamic loading characteristic of these events. This effort details the results from a series of 23 high-rate compression tests on vertebral body specimen. A high-rate servo-hydraulic test system applied a range of compressive loading rates (.01 mm/s to 1238 mm/s) to vertebral bodies in the thoracolumbar region (T7-L5). The force-deflection curves generated indicate rate dependent sensitivity of vertebral stiffness, ultimate load and ultimate deflection. Specimen subjected to high-rate dynamic loading to failure experienced critical structural damage at 5.5% ± 2.1% deflection. Compared to quasi-static loading, vertebral bodies had greater stiffness, greater force to failure, and lower ultimate failure deflection at high rates. Post-failure, an average loss in height of 15% was observed, along with a mean reduction in strength of 48%. The resulting data from these tests will allow for enhanced biofidelity of computational models by characterizing the vertebral stiffness response and ultimate deflection at rates representative of UBB events.

Development of a miniaturized position sensing system for measuring brain motion during impact - biomed 2013.

Since 2000, the Department of Defense has documented more than 253,000 cases of Traumatic Brain Injury (TBI). A significant portion of these injuries were attributed to explosive events, yet ninety-eight percent were non-penetrating. Understanding the response of the brain to blast events is critical, yet the mechanisms of brain injury from explosive trauma are poorly understood. This knowledge gap has led to an increased research focus on devices capable of investigating human brain response to non-penetrating, blast-induced loading. Furthermore, traumatic brain injury is a major issue for the civilian population as well with over 1.7 million cases of TBI per year in the US, primarily from falls and motor vehicle accidents. Current head surrogates and instrumentation are incapable of directly measuring critical parameters associated with TBI, such as brain motion, during dynamic loading. To this end, a novel sensor system for measuring brain motion inside of a human head surrogate was conceptualized and developed. The positioning system is comprised of a set of three fixed “generator” coils and a plurality of mobile, miniaturized “receiver” coil triads. Each generator coil transmits a sinusoidal electromagnetic signal at a unique frequency, and groups of three orthogonally arranged “receiver” coils detect these signals. Because of the oscillatory nature of these signals, the magnetic flux through the coil is always changing, allowing the application of Faraday’s Law of Induction and the point dipole model of an electric field to model the strength and direction of the field vector at any given point. Thus, the strength of the signal measured by a particular receiver coil depends on its position and orientation relative to the fixed position of the generators. These predictable changes are used to determine the six degrees of freedom (6-DOF) motion of the receiver. To calibrate and validate the system, a receiver coil was moved about in a controlled manner, and its actual position recorded by optical methods. Comparing the known position to the computed position at each time instance, a set of calibration constants were developed for each receiver triad. These constants were then utilized to convert receiver signal data into actual receiver position and orientation. Comparing this test case and several others like it, mean error was determined to be almost always less than 1.0 mm, and less than 0.5 mm >85% of the time. Additionally, high rate validation was conducted to confirm operation of the system in the impact domain. A coil was accelerated to approximately 15 m/sec along a fixed axis by ballistic impact and tracked by high speed video. The computed position was within 1 mm of the actual position 93% of the time and within 0.5 mm 83% of the time. The successful development and calibration of this sensing system now enables the direct measurements of brain displacement due to mechanical insults applied to a human head surrogate.

Real-time implementation of biofidelic SA1 model for tactile feedback.

In order for the functionality of an upper-limb prosthesis to approach that of a real limb it must be able to, accurately and intuitively, convey sensory feedback to the limb user. This paper presents results of the real-time implementation of a 'biofidelic' model that describes mechanotransduction in Slowly Adapting Type 1 (SA1) afferent fibers. The model accurately predicts the timing of action potentials for arbitrary force or displacement stimuli and its output can be used as stimulation times for peripheral nerve stimulation by a neuroprosthetic device. The model performance was verified by comparing the predicted action potential (or spike) outputs against measured spike outputs for different vibratory stimuli. Furthermore experiments were conducted to show that, like real SA1 fibers, the model's spike rate varies according to input pressure and that a periodic 'tapping' stimulus evokes periodic spike outputs.

Conveying tactile feedback in sensorized hand neuroprostheses using a biofidelic model of mechanotransduction.

One approach to conveying tactile feedback from sensorized neural prostheses is to characterize the neural signals that would normally be produced in an intact limb and reproduce them through electrical stimulation of the residual peripheral nerves. Toward this end, we have developed a model that accurately replicates the neural activity evoked by any dynamic stimulus in the three types of mechanoreceptive afferents that innervate the glabrous skin of the hand. The model takes as input the position of the stimulus as a function of time, along with its first (velocity), second (acceleration), and third (jerk) derivatives. This input is filtered and passed through an integrate-and-fire mechanism to generate a train of spikes as output. The major conclusion of this study is that the timing of individual spikes evoked in mechanoreceptive fibers innervating the hand can be accurately predicted by this model. We discuss how this model can be integrated in a sensorized prosthesis and show that the activity in a population of simulated afferents conveys information about the location, timing, and magnitude of contact between the hand and an object.