We gratefully acknowledge funding from the Natural Science and Engineering Research Council (NSERC) of Canada (Discovery Grants 435921), the Pashby Sport Safety Fund (2016: RES0028760), the Banting Research Foundation (Discovery Award 31214), NBEC Inc. (Canada), and the Faculty of Engineering and Department of Mechanical Engineering at the University of Alberta.

1. Helmet Fit Scenarios Arrangement
<ol>
	<li>Define fit scenarios to be studied on an anthropometric test device head and neck (Hybrid III 50th percentile male) with a head circumference of 575 mm. 
	NOTE: An example of four fit scenarios is shown in Table 1 with helmet positions corresponding to Figure 1. The forward and backward fit scenarios were based on definitions of correct helmet use from previous epidemiological studies, which specified proper helmet position as not covering the eyebrows or exposing the forehead3.</li>
	<li>For each scenario, mark each helmet position on the headform to ensure the helmet fit scenario is consistently repeated.</li>
	<li>Use a CPSC certified helmet, available in universal and extra-large sizes, for all fit scenarios. 
	NOTE: According to the manufacturer provided fit guide, a universal size most appropriately fits the headform circumference.
	<ol>
		<li>For each fit scenario, keep other fit parameters consistent. Specifically, tighten the chinstrap to leave approximately one finger width of space under the chin and hand-tighten the adjustable dial to maintain a secure fit.</li>
	</ol>
	</li>
</ol>
2. Fit Force Measurement
<ol>
	<li>Arrange five fit sensors on the skin of the headform, positioned on the front, back, left, right and top (Figure 2). 
	NOTE: The sensors are a modified version of Bragg grating force transducers developed within the research group19,20,21,22, optimized to measure fit forces over a range of 0 to 50 N. The modified sensors have a thickness and diameter of 2.6 mm and 14 mm respectively.</li>
	<li>Take a reference measurement with the transducers on the un-helmeted headform under no load. Take this reference measurement prior to each fit force measurement.</li>
	<li>Place the helmet onto the headform and measure force data for 3 s at a rate of 2.5 kHz. Repeat the same fit scenario six times for repeated measurements.</li>
	<li>Repeat the same measurement procedure for all fit scenarios.</li>
	<li>Convert wavelength shift data to force measurements by multiplying the measured wavelengths from the transducer by the pre-determined calibration constant for the fit force transducer.</li>
</ol>
3. Drop Tower for Impact Simulation
<ol>
	<li>Simulate impact to the helmeted head by linearly guiding the headform to hit an impact surface19,23. The equipment required to do this is context specific, as detailed below.
	<ol>
		<li>Assemble a drop tower to consist of an adjustable drop gimbal, an anthropometric test device head and neck, and a variable impact surface. 
		NOTE: The total drop assembly mass is approximately 11 kg. The added mass of the gimbal accounts for the exclusion of the full human body as an effective torso mass to better simulate a realistic impact24.</li>
		<li>Arrange 9 uni-axial accelerometers in a 3-2-2-2 configuration within the headform to allow linear and angular accelerations of the headform to be determined at the center of gravity25.</li>
		<li>Arrange a purpose built velocity gate on the impact tower to measure impact velocity immediately before impact.</li>
	</ol>
	</li>
	<li>Collect head acceleration and neck force/moment data using the data acquisition system. Filter analog voltages, sampled at 100 kHz for all channels. Prior to the data acquisition system, include a hardware anti-aliasing low pass filter with a corner frequency of 4 kHz26.</li>
	<li>Arrange the impact scenario.
	<ol>
		<li>For all impacts, remove the helmet visor to allow for better visibility during motion tracking. The effect of the visor during impact is assumed to be negligible due to its loose attachment.</li>
		<li>Arrange all drops to impact the forehead. This is a common impact location in cycling27, although other scenarios could also be simulated.</li>
		<li>Simulate six different impact scenarios by varying impact speed, impact surface, and either head-first or torso-first impacts as per Table 2.</li>
		<li>Raise the headform to the appropriate height, corresponding to specified impact velocities. Drop the headform from an appropriate height, typically 0.82 m and 1.83 m, to achieve velocities of 4 m/s and 6 m/s, respectively. 
		NOTE: Add height as necessary to overcome friction losses. Two impact velocities of 4 m/s and 6 m/s can be chosen based off previous literature and standards28.</li>
		<li>Arrange the impact surface.
		<ol>
			<li>Arrange either a flat or a 45&#176; angled anvil (Figure 4). The flat anvil simulates falls on a flat surface, while the angled anvil simulates impacts with a tangential velocity component.</li>
			<li>Cover both of the surfaces of the anvils in abrasive tape to simulate an asphalt surface. Adjust the anvil position as necessary between impacts to ensure the helmet to be impacted contacts only the flat surface of the anvil.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Arrange the drop tower for either head-first or torso-first impact. Simulate both head-first and torso-first impacts, with torso impacts similar to the combined loading impact configuration presented in Smith et al.18
	<ol>
		<li>To simulate a head-first impact, do not adjust the drop tower.</li>
		<li>To simulate the torso hitting the ground before the head, place a wooden block in the path of the drop gimbal. Place this wooden block at a height such that the head is approximately 25 mm away from impacting the anvil at the torso-impact. The head will then continue to hit the anvil by means of neck flexion only.</li>
		<li>Include a layer of foam to minimize vibrations from the drop tower (Figure 5).</li>
		<li>In contrast to head-first impacts, adjust the angle of the neck in torso-first impacts. 
		NOTE: This neck angle adjustment allows for the head to impact the anvil on the forehead after flexion, so that impact location is comparable to the head-first impact case (Figure 6). In addition to forehead impacts, this torso-first scenario would certainly be relevant in side impacts as well. In both head-first and torso-first impacts, this gimbal system allows for movement of the head and neck along the track after impact.</li>
	</ol>
	</li>
	<li>Trigger the data acquisition system, high speed cameras (see section 4), and drop of the headform simultaneously. Repeat the same impact and fit scenario configuration 3 times with new helmets each time. 
	NOTE: The high-speed cameras will need to be set up concurrently with the drop tower, detailed in section 4.</li>
	<li>Subject each of the four fit scenarios to each of the 6 different impact scenarios. Perform a total of 72 drops after 3 trials of each configuration.</li>
	<li>Post-process the headform kinematic and kinetic data.
	<ol>
		<li>Filter analog signals for acceleration and force/moment subsequently using a 4th order Butterworth filter in post processing to meet industry suggested practice26. Filter head accelerations and neck forces as per Channel Frequency Class (CFC) 1000. Filter neck moments as per CFC 600.</li>
	</ol>
	</li>
</ol>
4. Motion Capture Using a High Speed Dual Camera System
NOTE: Recording marker positions from two high speed cameras allow three-dimensional marker positions to be determined with the DLT method16 in post-processing. To determine head-helmet displacements, track markers on both the headform and helmet during impact.
<ol>
	<li>Arrange high-speed cameras around the drop tower.
	<ol>
		<li>Arrange two high-speed cameras around the drop tower to capture synchronized images of the helmet and headform movement during impact.
		<ol>
			<li>Place a master camera to the side of the drop tower and place a slave camera at approximately 45&#176; from the master (Figure 7). Setup a 250 W light between the cameras to allow for sufficient exposure.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Configure high speed cameras.
	<ol>
		<li>Equip each camera with either a 50 mm f/1.4 or 100 mm f/2.0 macro lens, depending on the field of view required. Set the apertures on the lenses at f/8.0. 
		NOTE: This aperture allows for sufficiently sharp focus in the desired depth of field. The required field of view ranged from 30-60 cm, depending on the impact scenario.</li>
		<li>Configure both cameras to record at 1280 x 800 pixels at a frame rate of 1000 frames per second or faster. Thus, the maximum exposure time per frame will be 600 &#181;s.</li>
		<li>Synchronize the two cameras in frames and internal clock. Set up a trigger so that both cameras trigger simultaneously.</li>
	</ol>
	</li>
	<li>Calibrate the space by taking a still image of a calibration frame from each camera. 
	NOTE: For the direct linear transformation (DLT) method, the space must be initially calibrated.
	<ol>
		<li>Move a calibration cage with 17 known calibration point locations into the field of view of both cameras and take a single image from each camera. A minimum of 11 common points must be visible from both cameras.</li>
		<li>Find the two-dimensional coordinates of each marker with tracking software. 
		NOTE: A coordinate measuring machine (CMM) determines the point locations of the calibration cage prior to DLT calibration.</li>
		<li>Using a series of calculations performed with the calibration markers&#39; coordinates (known as DLT)16, transform any two dimensional marker locations into three-dimensional coordinates relative to the calibration cage coordinate system in post-processing.</li>
	</ol>
	</li>
	<li>To quantify helmet displacement, track the distance between a point on the headform forehead and the brim of the helmet using the tracking software. 
	NOTE: Because these points are not visible from both cameras, track a set of three visible markers on each the headform and helmet instead. The points on the forehead and helmet can then be indirectly tracked.</li>
	<li>Place motion tracking markers on the headform and take a still reference image of the headform from each camera.
	<ol>
		<li>For this method of indirect marker tracking, take a headform reference image with each camera. Ensure that this reference image consists of three markers and a reference marker defined on the head.</li>
		<li>Maximize the distance between markers using three reference point locations while remaining in both cameras&#39; field of views. 
		NOTE: Maximizing the distance allows for better accuracy by decreasing indirect marker tracking sensitivity to tracking errors. The three markers allow for the three-dimensional reconstruction of motion in post processing, as well as the estimation of the forehead location.</li>
		<li>Hold the reference marker between the eyes on the lower forehead and the other markers spread across the headform. Ensure that these three other markers are visible from both cameras throughout an impact (Figure 8).</li>
	</ol>
	</li>
	<li>Place motion tracking markers on the helmet and take still reference images of the helmet from each camera as described for the headform reference (section 4.5).
	<ol>
		<li>Ensure that the reference consists of viewing at least four motion tracking markers. Hold one marker on the bottom of the helmet brim as a reference and spread the other three markers on the helmet. Ensure that these three markers are visible from both cameras throughout an impact. Take a single image from each camera for the helmet reference (Figure 9).</li>
	</ol>
	</li>
	<li>Trigger the data acquisition system, high speed cameras, and drop of the headform simultaneously as described in section 3. 
	NOTE: The drop tower will need to be set up concurrently with the high-speed cameras. After taking reference images, a drop may be performed.
	<ol>
		<li>Arrange the helmet fit scenario. Record the drop. Signal a trigger to the cameras manually upon impact. Arrange recording so that 3 s is recorded prior to the trigger and 8 s is recorded after the trigger. Manually review and bracket the synchronized camera images to contain the impact only.</li>
	</ol>
	</li>
</ol>
5. Head-helmet Marker Tracking and Post-processing
<ol>
	<li>Track head and helmet markers throughout the impact, using camera-specific software.
	<ol>
		<li>Track six points per drop: three on both the helmet and headform (Figure 10). With the software, determine the transient two-dimensional pixel coordinates of each marker.</li>
	</ol>
	</li>
	<li>Use the DLT method to calculate three-dimensional coordinates of tracked markers during a drop. 
	NOTE: With the calibration data from the calibration cage and the drop data from the two cameras, the DLT method can determine the three-dimensional coordinates of the tracked markers during a drop.</li>
	<li>Use the SVD (singular value decomposition) method17 to calculate the 3-D dimensional coordinates of the headform forehead and helmet brim. The difference between these two points is head-helmet displacement.
	<ol>
		<li>Use the SVD method to estimate the location of a reference point on each the headform forehead and helmet brim from the tracked markers.</li>
		<li>Use the SVD method to find the transformation matrix of the three markers between the reference frame and each individual frame of a drop. This transformation can be applied to find either the forehead or helmet brim locations.</li>
	</ol>
	</li>
	<li>Perform this indirect tracking on both the helmet and headform. The displacement between the forehead and helmet brim can then be monitored (Figure 11).</li>
</ol>

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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+comparison+of+Hybrid+III+and+National+Operating+Committee+on+Standards+for+Athletic+Equipment+headform+shape+characteristics+and+implications+on+football+helmet+fit.">Quantitative comparison of Hybrid III and National Operating Committee on Standards for Athletic Equipment headform shape characteristics and implications on football helmet fit.</a> Proc. Inst. Mech. Eng. Part P J. Sports Eng. Technol. 229 (1), 39-46 (2015).</li><li>Cobb, B. R., Zadnik, A. M., Rowson, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+analysis+of+helmeted+impact+response+of+Hybrid+III+and+National+Operating+Committee+on+Standards+for+Athletic+Equipment+headforms.">Comparative analysis of helmeted impact response of Hybrid III and National Operating Committee on Standards for Athletic Equipment headforms.</a> Proc. Inst. Mech. Eng. Part P J. Sports Eng. Technol. 230 (1), 50-60 (2016).</li><li>de Jager, M., Sauren, A., Thunnissen, J., Wismans, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+and+a+Detailed+Mathematical+Model+for+Head-Neck+Dynamics.">Global and a Detailed Mathematical Model for Head-Neck Dynamics.</a> Proc. Stapp Car Crash Conf. 40, 269-281 (1996).</li><li>Aare, M., Halldin, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+New+Laboratory+Rig+for+Evaluating+Helmets+Subject+to+Oblique+Impacts.">A New Laboratory Rig for Evaluating Helmets Subject to Oblique Impacts.</a> Traffic Inj. Prev. 4 (3), 240-248 (2003).</li></ol>

The authors have no conflicts to disclose and do not stand to gain financially from the publication of this work.

Here, methods for investigating helmet fit in simulated helmeted head impacts are presented. Helmet fit was quantified with fit force sensors, impacts were simulated with an ATD headform and neck on a guided drop tower, and helmet movement was tracked with high speed video. Different impact scenarios were simulated under different fit scenarios to investigate the effects on biomechanical measures of helmet fit.
The helmet fit sensors are capable of distinguishing differences in fit forces betw...

Most epidemiological evidence suggests bicycle helmets provide protection against head injuries for cyclists of all ages1. The biomechanical literature presents the consistent theme that the helmeted head sustains relatively less severe head/brain injuries secondary to impact, relative to the unprotected (un-helmeted) head2. Some research suggests that poor helmet fit is associated with an increased risk of head injury3, implying that helmets are most effective when fit properly. Depending on the criteria used to define good helmet fit, incorrect helmet use was found to be as high as 64% among helmeted cyclists3. Despite epidemiological evidence suggesting that helmet fit is relevant in the severity or likelihood of head injury in an impact, there is minimal experimental work assessing in a controlled laboratory setting whether or not correct helmet fit or helmet retention has a significant effect on biomechanical measures of injury. One related study investigates the effect of motorcycle helmet sizing during helmeted impacts simulated with a finite element model4. Another related study investigates the effect of helmet sizing during experimental impacts5 while using pressure sensitive film to quantify fit forces in football helmets. The effect of retention systems in bicycle and motorcycle helmet impacts have been investigated6,7, as well as a backward fit scenario for preadolescents6.
Our work proposes methods to study the effect of bicycle helmet fit on the risk of injury with helmet fit force sensors, simulated impacts with an anthropometric head and neck, and stereoscopic high-speed cameras. The goals of our proposed methods are to quantify fit and evaluate the risk of injury in different realistic impact scenarios. In contrast to related methods, our work investigates bicycle helmet fit, where proper helmet use is varied. Similar to previous methods, head kinematics are determined; however, neck loading and head-helmet displacements are also quantified. Although the epidemiology of neck injury in cycling suggests that neck injuries are uncommon, they tend to be associated with more severe head impacts and hospitalization8,9. The evidence is mixed on whether or not helmet use reduces rates of neck injury8 and none of the cited epidemiological studies quantify aspects of helmet fit. Considering the fact that neck injury in cycling tends to be associated with more severe accidents and that helmet fit has not been examined in neck injury epidemiology, methods for examining both head and neck injury are valuable in biomechanical research. Such experimental methods could be used in biomechanical studies that complement epidemiological studies which cannot in all cases control for impact severity or helmet fit.
In our work, a novel method of monitoring relative motions between the head and helmet during impact has been developed. The ability to monitor whether or not the helmet moves on the head can give valuable insight into both helmet stability and exposure of the unprotected head to injury during impact. In a study investigating helmet fit, helmet stability and head exposure are particularly valuable in evaluating helmet performance. In contrast to related work, different impact and fit scenarios emphasizing varied helmet positioning will also be tested.
Currently, correct helmet fit is subjective and nonspecifically defined. Generally, good helmet fit is characterized by stability and position. The helmet should be resistant to movement once secured on the head, and should be positioned such that the eyebrows are not covered and the forehead is not excessively exposed. Furthermore, approximately one-finger width of space should fit between the chin and chinstrap3. Measures of quantifying helmet fit are not widespread; other than force, methods may compare helmet fit based on comparing head and helmet geometry. One such method is the Helmet Fit Index proposed by Ellena et al.10. Our proposed method of quantifying helmet fit, fit force sensors, creates an objective means of comparing different helmet fit scenarios in the form of average and standard deviation of forces exerted on the head. These fit force values represent the tightness of a helmet, as well as the variation of tightness experienced on the head. These sensors provide a quantified comparison of forces that can be made between different fit scenarios. A secure tight fitting helmet would show higher forces while a loose helmet would show lower forces. This method of fit force measurement is similar to the Average Fit Index proposed by Jadischke5. However, Jadischke&#39;s methods utilize pressure sensitive film. The optical sensors we present allow unobtrusive measurement of fit force around the head or helmet.
For certification of helmets, a helmet is secured on an instrumented headform, which is then raised to a certain height to be dropped. The head and helmet is then subject to a free fall drop onto an anvil while recording linear accelerations. Although not typically used in helmet industry standards, a Hybrid III head (headform) and neck assembly were used in this work, with a guided drop tower to simulate impacts. In contrast to standards that typically use linear kinematics, the headform accelerometer array also allows the determination of rotational kinematics, a key parameter in predicting the likelihood of diffuse brain injuries, including concussion11. Through measurement of both linear acceleration and rotational acceleration and velocity, estimates of severe focal and diffuse head injury can be made by comparing kinematics to the several proposed kinematics-based injury assessment methods in the literature12,13. While the headform was originally developed for automotive crash testing, its use in helmet assessment and estimation of head injury risk in helmeted impact is well documented2,14. The impact simulation setup also includes an upper neck load cell, allowing the forces and moments associated with neck injury to be measured. Neck injury risk can then be estimated by comparing neck kinetics to injury assessment data from automotive injury data12,13.
A method of tracking helmet movement relative to the head during impact with high speed video is also proposed. Currently, no quantitative methods exist to evaluate helmet stability during impact. The Consumer Product Safety Commission (CPSC)15 bicycle helmet standard calls for a positional stability test, but is not representative of an impact. Furthermore, whether or not the helmet comes off the headform is the only result measured by the test. Regardless of exposure of the head to injury, a helmet may still pass as long as it stays on the headform during tests. The proposed method of tracking helmet movement is similar to Helmet Position Index (HPI)15 and measures the distance between the brim of a helmet and the forehead. This head-helmet displacement is tracked using high-speed video footage throughout an impact in order to obtain a representation of helmet stability and head exposure during impact. Using Direct Linear Transform (DLT)16 and Single Value Decomposition (SVD)17 methods, markers are tracked from two cameras to determine point locations in three-dimensional space and then the relative displacement between helmet and head.
Several impact severity and fit parameters are investigated. The impact scenarios include two impact speeds, two impacting anvil surfaces, and both torso-first and head-first impacts. In addition to a typical flat anvil surface, an angled anvil impact is also simulated to induce a tangential force component. A torso-first impact, as opposed to a head-first impact, is included to simulate a scenario in which a rider&#39;s shoulder impacts the ground before the head, similarly performed in previous work18. Finally, these four helmet fit scenarios are investigated: a regular fit, an oversized fit, a forward fit, and a backward fit. Unlike previous work, helmet positioning on the head is an investigated parameter, as well as helmet fit and helmet sizing.

<table><tbody><tr><td>Hybrid III Headform</td><td>Humanetics or Jasti-Utama</td><td>N/A</td><td>50th Percentile ATD, for impact simulation</td></tr><tr><td>Hybrid III Neck</td><td>Humanetics or Jasti-Utama</td><td>N/A</td><td>50th Percentile ATD, for impact simulation</td></tr><tr><td>Linear Accelerometers</td><td>Measurement Specialties</td><td>64C-2000-360</td><td>for head acceleration measurement</td></tr><tr><td>Upper Neck Load Cell</td><td>mg Sensor</td><td>N6ALB11A</td><td>for neck load measurement</td></tr><tr><td>High Speed Camera</td><td>Vision Research</td><td>v611</td><td>for motion capture</td></tr><tr><td>Camera Lens</td><td>Carl Zeiss</td><td>N/A</td><td>50 mm f1/.4, for motion capture</td></tr><tr><td>Camera Lens</td><td>Carl Zeiss</td><td>N/A</td><td>100 mm f/2.0, for motion capture</td></tr><tr><td>Bicycle Helmet</td><td>Bell</td><td>N/A</td><td>Traverse</td></tr><tr><td>Data Acquisition System</td><td>National Instruments</td><td>PXI 6251</td><td>for Hybrid III signal acquisition</td></tr><tr><td>Head Impact Drop Tower</td><td>University of Alberta</td><td>N/A</td><td>Custom-designed, for impact simulation</td></tr><tr><td>Optical Interrogator</td><td>Smart Fibres Ltd.</td><td>N/A</td><td>SmartScan, for optical sensor force measurement</td></tr><tr><td>Fit Force Sensor</td><td>University of Alberta</td><td>N/A</td><td>Custom-designed, for measuring helmet fit forces</td></tr></tbody></table>

a test bed to examine helmet fit and retention and biomechanical measures of head and neck injury in simulated impact

Conventional wisdom and the language in international helmet testing and certification standards suggest that appropriate helmet fit and retention during an impact are important factors in protecting the helmet wearer from impact-induced injury. This manuscript aims to investigate impact-induced injury mechanisms in different helmet fit scenarios through analysis of simulated helmeted impacts with an anthropometric test device (ATD), an array of headform acceleration transducers and neck force/moment transducers, a dual high speed camera system, and helmet-fit force sensors developed in our research group based on Bragg gratings in optical fiber. To simulate impacts, an instrumented headform and flexible neck fall along a linear guide rail onto an anvil. The test bed allows simulation of head impact at speeds up to 8.3 m/s, onto impact surfaces that are both flat and angled. The headform is fit with a crash helmet and several fit scenarios can be simulated by making context specific adjustments to the helmet position index and/or helmet size. To quantify helmet retention, the movement of the helmet on the head is quantified using post-hoc image analysis. To quantify head and neck injury potential, biomechanical measures based on headform acceleration and neck force/moment are measured. These biomechanical measures, through comparison with established human tolerance curves, can estimate the risk of severe life threatening and/or mild diffuse brain injury and osteoligamentous neck injury. To our knowledge, the presented test-bed is the first developed specifically to assess biomechanical effects on head and neck injury relative to helmet fit and retention.

Fit Force Measurement 
For each fit scenario, fit force measurement was performed at each sensor location (Figure 12) and a t-test, assuming unequal variances, was performed to determine significance (p &#60; 0.05). The average standard deviation across all measurements was &#177; 0.14 N. Higher fit forces indicate a tighter fit.
Head Kinematic and Neck Kinetic Data</st...

Watch this Scientific Journal Video about A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact at JoVE.com

A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact

Using an anthropometric head and neck, optical fiber-based fit force transducers, an array of head acceleration and neck force/moment transducers, and a dual high speed camera system, we present a test bed to study helmet retention and effects on biomechanical measures of head and neck injury secondary to head impact.

Conventional wisdom and the language in international helmet testing and certification standards suggest that appropriate helmet fit and retention during ...

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Research

JoVE Journal

Bioengineering

8.9K Views.  University of Alberta. Using an anthropometric head and neck, optical fiber-based fit force transducers, an array of head acceleration and neck force/moment transducers, and a dual high speed camera system, we present a test bed to study helmet retention and effects on biomechanical measures of head and neck injury secondary to head impact.

Video: A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact

An Investigation of the Effects of Sports-related Concussion in Youth Using Functional Magnetic Resonance Imaging and the Head Impact Telemetry System

One of the most commonly reported injuries in children who participate in sports is concussion or mild traumatic brain injury (mTBI)1. Children and youth involved in organized sports such as competitive hockey are nearly six times more likely to suffer a severe concussion compared to children involved in other leisure physical activities2. While the most common cognitive sequelae of mTBI appear similar for children and adults, the recovery profile and breadth of consequences in children remains largely unknown2, as does the influence of pre-injury characteristics (e.g. gender) and injury details (e.g. magnitude and direction of impact) on long-term outcomes. Competitive sports, such as hockey, allow the rare opportunity to utilize a pre-post design to obtain pre-injury data before concussion occurs on youth characteristics and functioning and to relate this to outcome following injury. Our primary goals are to refine pediatric concussion diagnosis and management based on research evidence that is specific to children and youth. To do this we use new, multi-modal and integrative approaches that will:
 1.Evaluate the immediate effects of head trauma in youth 
2.Monitor the resolution of post-concussion symptoms (PCS) and cognitive performance during recovery 
3.Utilize new methods to verify brain injury and recovery
To achieve our goals, we have implemented the Head Impact Telemetry (HIT) System. (Simbex; Lebanon, NH, USA). This system equips commercially available Easton S9 hockey helmets (Easton-Bell Sports; Van Nuys, CA, USA) with single-axis accelerometers designed to measure real-time head accelerations during contact sport participation 3 - 5. By using telemetric technology, the magnitude of acceleration and location of all head impacts during sport participation can be objectively detected and recorded. We also use functional magnetic resonance imaging (fMRI) to localize and assess changes in neural activity specifically in the medial temporal and frontal lobes during the performance of cognitive tasks, since those are the cerebral regions most sensitive to concussive head injury 6. Finally, we are acquiring structural imaging data sensitive to damage in brain white matter.

This article provides an overview of a multi-modal approach to mild traumatic brain injury diagnosis and recovery in youth. This approach combines neuropsychological testing with functional magnetic resonance imaging and the Head Impact Telemetry System to monitor the relationship between head impacts and brain activity during cognitive testing.

One of the most commonly reported injuries in children who participate in sports is concussion or mild traumatic brain injury (mTBI)1. Children and youth ...

Medicine

Creating Two-Dimensional Patterned Substrates for Protein and Cell Confinement

Microcontact printing provides a rapid, highly reproducible method for the creation of well-defined patterned substrates.1 While microcontact printing can be employed to directly print a large number of molecules, including proteins,2 DNA,3 and silanes,4 the formation of self-assembled monolayers (SAMs) from long chain alkane thiols on gold provides a simple way to confine proteins and cells to specific patterns containing adhesive and resistant regions. This confinement can be used to control cell morphology and is useful for examining a variety of questions in protein and cell biology. Here, we describe a general method for the creation of well-defined protein patterns for cellular studies.5 This process involves three steps: the production of a patterned master using photolithography, the creation of a PDMS stamp, and microcontact printing of a gold-coated substrate. Once patterned, these cell culture substrates are capable of confining proteins and/or cells (primary cells or cell lines) to the pattern.
The use of self-assembled monolayer chemistry allows for precise control over the patterned protein/cell adhesive regions and non-adhesive regions; this cannot be achieved using direct protein stamping. Hexadecanethiol, the long chain alkane thiol used in the microcontact printing step, produces a hydrophobic surface that readily adsorbs protein from solution. The glycol-terminated thiol, used for backfilling the non-printed regions of the substrate, creates a monolayer that is resistant to protein adsorption and therefore cell growth.6 These thiol monomers produce highly structured monolayers that precisely define regions of the substrate that can support protein adsorption and cell growth. As a result, these substrates are useful for a wide variety of applications from the study of intercellular behavior7 to the creation of microelectronics.8
While other types of monolayer chemistry have been used for cell culture studies, including work from our group using trichlorosilanes to create patterns directly on glass substrates,9 patterned monolayers formed from alkane thiols on gold are straight-forward to prepare. Moreover, the monomers used for monolayer preparation are commercially available, stable, and do not require storage or handling under inert atmosphere. Patterned substrates prepared from alkane thiols can also be recycled and reused several times, maintaining cell confinement.10

Self-assembled monolayers (SAMs) formed from long chain alkane thiols on gold provide well-defined substrates for the formation of protein patterns and cell confinement. Microcontact printing of hexadecanethiol using a polydimethylsiloxane (PDMS) stamp followed by backfilling with a glycol-terminated alkane thiol monomer produces a pattern where protein and cells adsorb only to the stamped hexadecanethiol region.

Microcontact printing provides a rapid, highly reproducible method for the creation of well-defined patterned substrates.1  While microcontact printing ...

In Vivo Protocol of Controlled Subconcussive Head Impacts for the Validation of Field Study Data

Subconcussive hits pose a threat to neuronal health as they have shown to induce neuronal structural damage and functional impairment without causing outward symptomology and appear to be a key contributor to an irreversible neurodegenerative disease, chronic traumatic encephalopathy (CTE). In addition, athletes can incur more than 1,000 of these hits per season. The subconcussive soccer heading model (SSHM) is a relevant, reproducible, and leading method of isolating and examining the effects of these subconcussive head impacts. By controlling variables such as ball traveling speed, the frequency of impacts, interval, ball placement to the head, as well as by measuring head impact magnitude, the SSHM provides the scientific community with a superior avenue of investigating the acute subconcussive effects on neuronal health. In this paper, we demonstrate the utility of SSHM in studying a time-course expression of neurofilament-light polypeptide (NF-L) in plasma in a repeated measures fashion. NF-L is an axonal injury marker that has previously been shown to be elevated in boxers and football players following subconcussive head trauma. Thirty-four adult aged soccer players were recruited and randomly assigned to either a soccer heading (n = 18) or kicking (n = 16) group. The heading group executed 10 headers with soccer balls projected at a velocity of 25 mph over 10 min. The kicking group followed the same protocol with 10 kicks. Plasma samples were obtained before and at 0 h, 2 h, and 24 h after heading/kicking and assessed for NF-L expressions. The heading group showed a gradual increase in plasma NF-L expression and peaked at 24 h after the heading protocol, whereas the kicking group remained consistent across the time points. These results confirmed the NF-L data from clinical field studies, encouraging the use of SSHM to validate clinical subconcussion data.

The subconcussive soccer heading model is a safe and concise methodological approach to isolate and measure the effects of subconcussive head impacts.

Subconcussive hits pose a threat to neuronal health as they have shown to induce neuronal structural damage and functional impairment without causing ...

Behavior

Modified Drop Tower Impact Tests for American Football Helmets

A modified National Operating Committee on Standards for Athletic Equipment (NOCSAE) test method for American football helmet drop impact test standards is presented that would provide better assessment of a helmet's on-field impact performance by including a faceguard on the helmet. In this study, a merger of faceguard and helmet test standards is proposed. The need for a more robust systematic approach to football helmet testing procedures is emphasized by comparing representative results of the Head Injury Criterion (HIC), Severity Index (SI), and peak acceleration values for different helmets at different helmet locations under modified NOCSAE standard drop tower tests. Essentially, these comparative drop test results revealed that the faceguard adds a stiffening kinematic constraint to the shell that lessens total energy absorption. The current NOCSAE standard test methods can be improved to represent on-field helmet hits by attaching the faceguards to helmets and by including two new helmet impact locations (Front Top and Front Top Boss). The reported football helmet test method gives a more accurate representation of a helmet's performance and its ability to mitigate on-field impacts while promoting safer football helmets.

This article provides a novel technique to assess the performance characteristics of American football helmets by inclusion of faceguards during NOCSAE Standard drop tests. Additionally, two more impact locations are proposed to be added to the NOCSAE certification.

A modified National Operating Committee on Standards for Athletic Equipment (NOCSAE) test method for American football helmet drop impact test standards ...

Testing of all Six Semicircular Canals with Video Head Impulse Test Systems

Throughout the last decade, there has been a rapid development of existing test procedures and methods evaluating the human vestibular system. In 2009 and 2013, commercially available video Head Impulse Testing (vHIT) has enabled clinicians to examine the function of all three paired semicircular canals within the vestibular system. The vHIT test has revolutionized vestibular testing and, at many clinics and hospitals around the world, this test is now considered the most important initial test of vertiginous patients. There are several manufacturers of vHIT systems around the world. A test protocol for two of the most widespread vHIT systems, EyeSeeCam and ICS Impulse, will be presented. Included in this protocol is a description of the two different test methods termed 2D vHIT testing and 3D vHIT testing. The vHIT system includes a lightweight goggle with accompanying software. The test is fast (5-10 min) and can be done with minimal discomfort to the person being examined. However, there are many steps of the test, and each of these steps may alter the final test results, if the individual steps of the test are not performed correctly. It is therefore of paramount importance that the examiner is familiar with the potential noise and/or artifact triggers. Systematic training of future examiners before performing vHIT in a clinical setting and compliance with this protocol may minimize these challenges of the test. The vHIT test is not just a &#8220;plug and play&#8221; test. However, if carried out correctly, this test offers excellent objective assessment of the function of the high frequency domain of the vestibular system. It has a very high positive predictive value and offers a specificity very close to one hundred percent.

This protocol describes how to correctly perform the video head impulse test with two separate test systems commonly used worldwide. Both the 2D and 3D video head impulse test methods are described.

Throughout the last decade, there has been a rapid development of existing test procedures and methods evaluating the human vestibular system. In 2009 and ...

Low-intensity Blast Wave Model for Preclinical Assessment of Closed-head Mild Traumatic Brain Injury in Rodents

Traumatic brain injury (TBI) is a large-scale public health problem. Mild TBI is the most prevalent form of neurotrauma and accounts for a large number of medical visits in the United States. There are currently no FDA-approved treatments available for TBI. The increased incidence of military-related, blast-induced TBI further accentuates the urgent need for effective TBI treatments. Therefore, new preclinical TBI animal models that recapitulate aspects of human blast-related TBI will greatly advance the research efforts into the neurobiological and pathophysiological processes underlying mild to moderate TBI as well as the development of novel therapeutic strategies for TBI.
Here we present a reliable, reproducible model for the investigation of the molecular, cellular, and behavioral effects of mild to moderate blast-induced TBI. We describe a step-by-step protocol for closed-head, blast-induced mild TBI in rodents using a bench-top setup consisting of a gas-driven shock tube equipped with piezoelectric pressure sensors to ensure consistent test conditions. The benefits of the setup that we have established are its relative low-cost, ease of installation, ease of use and high-throughput capacity. Further advantages of this non-invasive TBI model include the scalability of the blast peak overpressure and the generation of controlled reproducible outcomes. The reproducibility and relevance of this TBI model has been evaluated in a number of downstream applications, including neurobiological, neuropathological, neurophysiological and behavioral analyses, supporting the use of this model for the characterization of processes underlying the etiology of mild to moderate TBI.

We present here a protocol of a blast wave model for rodents to investigate neurobiological and pathophysiological effects of mild to moderate traumatic brain injury. We established a gas-driven, bench-top setup equipped with pressure sensors allowing for reliable and reproducible generation of blast-induced mild to moderate traumatic brain injury.

Traumatic brain injury (TBI) is a large-scale public health problem. Mild TBI is the most prevalent form of neurotrauma and accounts for a large number of ...

Neuroscience

Assessing Changes in Synaptic Plasticity Using an Awake Closed-Head Injury Model of Mild Traumatic Brain Injury

Mild traumatic brain injuries (mTBIs) are a prevalent health issue in North America. There is increasing pressure to utilize ecologically valid models of closed-head mTBI in the preclinical setting to increase translatability to the clinical population. The awake closed-headed injury (ACHI) model uses a modified controlled cortical impactor to deliver closed-headed injury, inducing clinically relevant behavioral deficits without the need for a craniotomy or the use of an anesthetic.
This technique does not normally induce fatalities, skull fractures, or brain bleeds, and is more consistent with being a mild injury. Indeed, the mild nature of the ACHI procedure makes it ideal for studies investigating repetitive mTBI (r-mTBI). Growing evidence indicates that r-mTBI can result in a cumulative injury that produces behavioral symptoms, neuropathological changes, and neurodegeneration. r-mTBI is common in youths playing sports, and these injuries occur during a period of robust synaptic reorganization and myelination, making the younger population particularly vulnerable to the long-term influences of r-mTBI.
Further, r-mTBI occurs in cases of intimate partner violence, a condition for which there are few objective screening measures. In these experiments, synaptic function was assessed in the hippocampus in juvenile rats that had experienced r-mTBI using the ACHI model. Following the injuries, a tissue slicer was utilized to make hippocampal slices to evaluate bidirectional synaptic plasticity in the hippocampus at either 1 or 7 days following the r-mTBI. Overall, the ACHI model provides researchers with an ecologically valid model to study changes in synaptic plasticity following mTBI and r-mTBI.

Here, it is demonstrated how an awake closed-head injury model can be used for examining the effects of repeated mild traumatic brain injury (r-mTBI) on synaptic plasticity in the hippocampus. The model replicates important features of r-mTBI in patients and is used in conjunction with in vitro electrophysiology.

Mild traumatic brain injuries (mTBIs) are a prevalent health issue in North America. There is increasing pressure to utilize ecologically valid models of ...

Validating Injury Response and Behavioral Assessments in an mTBI Rat Model

Rat Model of Closed-Head Mild Traumatic Injury and its Validation

Animal models are crucial for advancing our understanding of mild traumatic brain injury (mTBI) and guiding clinical research. To achieve meaningful insights, developing a stable and reproducible animal model is essential. In this study, we report a detailed description of a closed-head mTBI model and a representative validation method using Sprague-Dawley rats to verify the modeling effect. The model involves dropping a 550 g mass weight from a height of 100 cm directly onto the head of a rat on a destructible surface, followed by a 180-degree turn. To assess the injury, rats underwent a series of neurobehavioral assessments 10 min post-injury, including time of loss of consciousness, first seeking-behavior time, escape ability, and beam balance ability test. During the acute and subacute stages following the injury, behavioral tests were conducted to assess motor coordination ability (Beam task), anxiety (Open Field test), and learning and memory abilities (Morris Water Maze test). The closed-head mTBI model produced a consistent injury response with minimal mortality and replicated real-life situations. The validation method effectively verified the model development and ensured the stability and consistency of the model.

Author Spotlight: Advancing Traumatic Brain Injury Research - A Closed-Head Model for Accurate Replication and Rapid Assessment 

Here, we present a closed-head mild traumatic brain injury (mTBI) rat model and its validation exhibiting remarkable similarity to human mTBI concerning behavioral manifestations during the acute and subacute stages.

Animal models are crucial for advancing our understanding of mild traumatic brain injury (mTBI) and guiding clinical research. To achieve meaningful ...

Development of an Uncomplicated Mild Traumatic Brain Injury Model Modified by Weight-Drop Method and Evidenced by Magnetic Resonance Imaging

Mild traumatic brain injury (mTBI), known as concussion, accounts for more than 85% of brain injuries globally. Specifically, uncomplicated mTBI showing negative findings in routine clinical imaging in the acute phase hinders early and appropriate care in these patients. It has been acknowledged that different impact parameters may affect and even accelerate the progress of subsequent neuropsychological symptoms following mTBI. However, the association of impact parameters during concussion to the outcome has not been extensively examined. In the current study, an animal model with closed-head injury (CHI) modified from the weight-drop injury paradigm was described and demonstrated in detail. Adult male Sprague-Dawley rats (n = 20) were randomly assigned to CHI groups with different impact parameters (n = 4 per group). Longitudinal MR imaging studies, including T2-weighted imaging and diffusion tensor imaging, and sequential behavioral assessments, such as modified neurological severity score (mNSS) and the beam walk test, were conducted over a 50-day study period. Immunohistochemical staining for astrogliosis was performed on day 50 post-injury. Worse behavioral performance was observed in animals following repetitive CHI compared to the single injury and sham group. By using longitudinal magnetic resonance imaging (MRI), no significant brain contusion was observed at 24 h post-injury. Nevertheless, cortical atrophy and alteration of cortical fractional anisotropy (FA) were demonstrated on day 50 post-injury, suggesting the successful replication of clinical uncomplicated mTBI. Most importantly, changes in neurobehavioral outcomes and image features observed after mTBI were dependent on impact number, inter-injury intervals, and the selected impact site in the animals. This in vivo mTBI model combined with preclinical MRI provides a means to explore brain injury on a whole-brain scale. It also allows the investigation of imaging biomarkers sensitive to mTBI across varying impact parameters and severity levels.

Here, we present a protocol to establish a closed-head injury animal model replicating the neuroimage outcome of uncomplicated mild traumatic brain injury with the preserved brain structure in the acute phase and long-term brain atrophy. Longitudinal magnetic resonance imaging is the primary method used for evidence.

Mild traumatic brain injury (mTBI), known as concussion, accounts for more than 85% of brain injuries globally. Specifically, uncomplicated mTBI showing ...

Modeling Repetitive Concussive Head Injuries in a Mouse Model

<a href='https://app.jove.com/v/54530/a-repetitive-concussive-head-injury-model-in-mice'>Source: Yang, Z., et.al.&#160;A Repetitive Concussive Head Injury Model in Mice. J. Vis. Exp. (2016).</a>This video demonstrates the induction of repetitive concussive head injuries in a mouse using an electromagnetic impact device. The procedure involves positioning the impact tip between the interfrontal and lambdoid sutures on the skull of an anesthetized mouse and using a probe tip to precisely set the impact depth. The impact is delivered at a controlled velocity and depth to simulate mild traumatic brain injuries, followed by a recovery period, with the injuries repeated at specified intervals.

Source: Yang, Z., et.al.&#160;A Repetitive Concussive Head Injury Model in Mice. J. Vis. Exp. (2016).This video demonstrates the induction of repetitive ...