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>

<ol>
	<li>Thompson, D. C., Rivara, F. P., Thompson, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effectiveness+of+Bicycle+Safety+Helmets+in+Preventing+Head+Injuries:+A+Case-Control+Study.">Effectiveness of Bicycle Safety Helmets in Preventing Head Injuries: A Case-Control Study.</a> JAMA. 276 (24), 1968-1973 (1996).</li><li>Cripton, P. A., Dressler, D. M., Stuart, C. A., Dennison, C. R., Richards, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bicycle+helmets+are+highly+effective+at+preventing+head+injury+during+head+impact:+Head-form+accelerations+and+injury+criteria+for+helmeted+and+unhelmeted+impacts.">Bicycle helmets are highly effective at preventing head injury during head impact: Head-form accelerations and injury criteria for helmeted and unhelmeted impacts.</a> Accid. Anal. Prev. 70, 1-7 (2014).</li><li>Lee, R. S., Hagel, B. E., Karkhaneh, M., Rowe, B. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+systematic+review+of+correct+bicycle+helmet+use:+how+varying+definitions+and+study+quality+influence+the+results.">A systematic review of correct bicycle helmet use: how varying definitions and study quality influence the results.</a> Inj. Prev. 15 (2), 125-131 (2009).</li><li>Chang, L. -. T., Chang, C. -. H., Chang, G. -. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fit+effect+of+motorcycle+helmet+-+A+finite+element+modeling.">Fit effect of motorcycle helmet - A finite element modeling.</a> JSME Int. J. Ser. Solid Mech. Mater. Eng. 44 (1), 185-192 (2001).</li><li>Testing of Bicycle Helmets for Preadolescents. IRCOBI Conf. Proc Available from: <a target="_blank" href="https://trid.trb.org/view.aspx?id=1370437">https://trid.trb.org/view.aspx?id=1370437</a> (2015)</li><li>McIntosh, A. S., Lai, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Motorcycle+Helmets:+Head+and+Neck+Dynamics+in+Helmeted+and+Unhelmeted+Oblique+Impacts.">Motorcycle Helmets: Head and Neck Dynamics in Helmeted and Unhelmeted Oblique Impacts.</a> Traffic Inj. Prev. 14 (8), 835-844 (2013).</li><li>Olivier, J., Creighton, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bicycle+injuries+and+helmet+use:+a+systematic+review+and+meta-analysis.">Bicycle injuries and helmet use: a systematic review and meta-analysis.</a> Int. J. Epidemiol. 46 (1), 278-292 (2017).</li><li>Rivara, F. P., Thompson, D. C., Thompson, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epidemiology+of+bicycle+injuries+and+risk+factors+for+serious+injury.">Epidemiology of bicycle injuries and risk factors for serious injury.</a> Inj. Prev. 3 (2), 110-114 (1997).</li><li>Ellena, T., Subic, A., Mustafa, H., Pang, T. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Helmet+Fit+Index+-+An+intelligent+tool+for+fit+assessment+and+design+customisation.">The Helmet Fit Index - An intelligent tool for fit assessment and design customisation.</a> Appl. Ergon. 55, 194-207 (2016).</li><li>Takhounts, E. G., Craig, M. J., Moorhouse, K., McFadden, J., Hasija, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+Brain+Injury+Criteria+(BrIC).">Development of Brain Injury Criteria (BrIC).</a> Stapp Car Crash J. 57, 243-266 (2013).</li><li>Eppinger, R., Sun, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Development of improved injury criteria for the assessment of advanced automotive restraint systems - II. , (1999).</li><li>Mertz, H. J., Irwin, A. L., Prasad, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomechanical+and+scaling+bases+for+frontal+and+side+impact+injury+assessment+reference+values.">Biomechanical and scaling bases for frontal and side impact injury assessment reference values.</a> Stapp Car Crash J. 47, 155 (2003).</li><li>Newman, J. A., Beusenberg, M. C., Shewchenko, N., Withnall, C., Fournier, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Verification+of+biomechanical+methods+employed+in+a+comprehensive+study+of+mild+traumatic+brain+injury+and+the+effectiveness+of+American+football+helmets.">Verification of biomechanical methods employed in a comprehensive study of mild traumatic brain injury and the effectiveness of American football helmets.</a> J. Biomech. 38 (7), 1469-1481 (2005).</li><li>CPSC. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Safety Standard for Bicycle Helmets; Final Rule. , (1998).</li><li>Miller, N. R., Shapiro, R., McLaughlin, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+technique+for+obtaining+spatial+parameters+of+segments+of+biomechanical+systems+from+cinematographic+data.">A technique for obtaining spatial parameters of segments of biomechanical systems from cinematographic data.</a> J. Biomech. 13, 535-547 (1980).</li><li>Arun, K. S., Huang, T. S., Blostein, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Least-Squares+Fitting+of+Two+3-D+Point+Sets.">Least-Squares Fitting of Two 3-D Point Sets.</a> IEEE Trans. Pattern Anal. Mach. Intell. 9 (5), 698-700 (1987).</li><li>Smith, T. A., Halstead, P. D., McCalley, E., Kebschull, S. A., Halstead, S., Killeffer, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Angular+head+motion+with+and+without+head+contact:+implications+for+brain+injury.">Angular head motion with and without head contact: implications for brain injury.</a> Sports Eng. 18 (3), 165-175 (2015).</li><li>Butz, R., Dennison, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-fibre+Bragg+grating+impact+force+transducer+for+studying+head-helmet+mechanical+interaction+in+head+impact.">In-fibre Bragg grating impact force transducer for studying head-helmet mechanical interaction in head impact.</a> J. Light. Technol. 33 (13), 8 (2015).</li><li>Butz, R. C., Knowles, B. M., Newman, J. A., Dennison, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+external+helmet+accessories+on+biomechanical+measures+of+head+injury+risk:+An+ATD+study+using+the+HYBRIDIII+headform.">Effects of external helmet accessories on biomechanical measures of head injury risk: An ATD study using the HYBRIDIII headform.</a> J. Biomech. 48 (14), 3816-3824 (2015).</li><li>Dennison, C. R., Wild, P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Superstructured+fiber-optic+contact+force+sensor+with+minimal+cosensitivity+to+temperature+and+axial+strain.">Superstructured fiber-optic contact force sensor with minimal cosensitivity to temperature and axial strain.</a> Appl. Opt. 51, 1188-1197 (2012).</li><li>Dennison, C. R., Wild, P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensitivity+of+Bragg+gratings+in+birefringent+optical+fibre+to+transverse+compression+between+conforming+materials.">Sensitivity of Bragg gratings in birefringent optical fibre to transverse compression between conforming materials.</a> Appl. Opt. 49, 2250-2261 (2010).</li><li>Knowles, B. M., Yu, H., Dennison, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accuracy+of+a+Wearable+Sensor+for+Measures+of+Head+Kinematics+and+Calculation+of+Brain+Tissue+Strain.">Accuracy of a Wearable Sensor for Measures of Head Kinematics and Calculation of Brain Tissue Strain.</a> J. Appl. Biomech. 33 (1), 2-11 (2017).</li><li>Nightingale, R. W., McElhaney, J. H., Richardson, W. J., Myers, B. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+responses+of+the+head+and+cervical+spine+to+axial+impact+loading.">Dynamic responses of the head and cervical spine to axial impact loading.</a> J. Biomech. 29, 307-318 (1996).</li><li>Padgaonkar, A. J., Krieger, K. W., King, A. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+Angular+Acceleration+of+a+Rigid+Body+Using+Linear+Accelerometers.">Measurement of Angular Acceleration of a Rigid Body Using Linear Accelerometers.</a> J. Appl. Mech. 42 (3), 552-556 (1975).</li><li>SAE. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> J211 Instrumentation for Impact Test - Part 1: Electronic Instrumentation. , (2014).</li><li>Depreitere, B., Lierde, C. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bicycle-related+head+injury:+a+study+of+86+cases.">Bicycle-related head injury: a study of 86 cases.</a> Accid. Anal. Prev. 36, 561-567 (2004).</li><li>Influence of Impact Velocity and Angle in a Detailed Reconstruction of a Bicycle Accident. Proc. 2012 Int. IRCOBI Conf. Biomech. Impacts Available from: <a target="_blank" href="https://lirias.kuleuven.be/handle/123456789/357473">https://lirias.kuleuven.be/handle/123456789/357473</a> (2012)</li><li>Newman, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Generalized+Model+for+Brain+Injury+Threshold+(GAMBIT).">A Generalized Model for Brain Injury Threshold (GAMBIT).</a> IRCOBI Conf. Proc. , (1986).</li><li>Newman, J. A., Shewchenko, N., Welbourne, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+proposed+New+Biomechanical+head+injury+assessment+function+-+the+maximum+power+index.">A proposed New Biomechanical head injury assessment function - the maximum power index.</a> Stapp Car Crash J. 44, 215-247 (2000).</li><li>NOCSAE. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Standard Test Method and Equipment used in Evaluating the Performance Characteristics of Protective Headgear/Equipment NOCSAE Doc (ND) 001- 11m12. , (2012).</li><li>Cobb, B. R., MacAlister, A., Young, T. J., Kemper, A. R., Rowson, S., Duma, S. 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/Jasti-Utama</td>
			<td>N/A</td>
			<td>50th Percentile ATD, for impact simulation</td>
		</tr>
		<tr>
			<td>Hybrid III Neck</td>
			<td>Humanetics/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 ...

a-test-bed-to-examine-helmet-fit-retention-biomechanical-measures

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

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 ...

Design of a Cyclic Pressure Bioreactor for the Ex Vivo Study of Aortic Heart Valves

The aortic valve, located between the left ventricle and the aorta, allows for unidirectional blood flow, preventing backflow into the ventricle. Aortic valve leaflets are composed of interstitial cells suspended within an extracellular matrix (ECM) and are lined with an endothelial cell monolayer. The valve withstands a harsh, dynamic environment and is constantly exposed to shear, flexion, tension, and compression. Research has shown calcific lesions in diseased valves occur in areas of high mechanical stress as a result of endothelial disruption or interstitial matrix damage1-3. Hence, it is not surprising that epidemiological studies have shown high blood pressure to be a leading risk factor in the onset of aortic valve disease4. 
The only treatment option currently available for valve disease is surgical replacement of the diseased valve with a bioprosthetic or mechanical valve5. Improved understanding of valve biology in response to physical stresses would help elucidate the mechanisms of valve pathogenesis. In turn, this could help in the development of non-invasive therapies such as pharmaceutical intervention or prevention. Several bioreactors have been previously developed to study the mechanobiology of native or engineered heart valves6-9. Pulsatile bioreactors have also been developed to study a range of tissues including cartilage10, bone11 and bladder12. The aim of this work was to develop a cyclic pressure system that could be used to elucidate the biological response of aortic valve leaflets to increased pressure loads. 
The system consisted of an acrylic chamber in which to place samples and produce cyclic pressure, viton diaphragm solenoid valves to control the timing of the pressure cycle, and a computer to control electrical devices. The pressure was monitored using a pressure transducer, and the signal was conditioned using a load cell conditioner. A LabVIEW program regulated the pressure using an analog device to pump compressed air into the system at the appropriate rate. The system mimicked the dynamic transvalvular pressure levels associated with the aortic valve; a saw tooth wave produced a gradual increase in pressure, typical of the transvalvular pressure gradient that is present across the valve during diastole, followed by a sharp pressure drop depicting valve opening in systole. The LabVIEW program allowed users to control the magnitude and frequency of cyclic pressure. The system was able to subject tissue samples to physiological and pathological pressure conditions. This device can be used to increase our understanding of how heart valves respond to changes in the local mechanical environment.

Design of a Cyclic Pressure Bioreactor for the Ex Vivo Study of Aortic Heart Valves

A cyclic pressure bioreactor capable of subjecting heart valve tissue to physiological and pathological pressure conditions has been designed. A LabVIEW program allows users to control pressure magnitude, amplitude and frequency. This device can be used to study the mechanobiology of heart valve tissue or isolated cells.

The aortic valve, located between the left ventricle and the aorta, allows for unidirectional blood flow, preventing backflow into the ventricle. Aortic ...

Directed Cellular Self-Assembly to Fabricate Cell-Derived Tissue Rings for Biomechanical Analysis and Tissue Engineering

Each year, hundreds of thousands of patients undergo coronary artery bypass surgery in the United States.1 Approximately one third of these patients do not have suitable autologous donor vessels due to disease progression or previous harvest. The aim of vascular tissue engineering is to develop a suitable alternative source for these bypass grafts. In addition, engineered vascular tissue may prove valuable as living vascular models to study cardiovascular diseases. Several promising approaches to engineering blood vessels have been explored, with many recent studies focusing on development and analysis of cell-based methods.2-5 Herein, we present a method to rapidly self-assemble cells into 3D tissue rings that can be used in vitro to model vascular tissues.
To do this, suspensions of smooth muscle cells are seeded into round-bottomed annular agarose wells. The non-adhesive properties of the agarose allow the cells to settle, aggregate and contract around a post at the center of the well to form a cohesive tissue ring.6,7 These rings can be cultured for several days prior to harvesting for mechanical, physiological, biochemical, or histological analysis. We have shown that these cell-derived tissue rings yield at 100-500 kPa ultimate tensile strength8 which exceeds the value reported for other tissue engineered vascular constructs cultured for similar durations (&lt;30 kPa).9,10 Our results demonstrate that robust cell-derived vascular tissue ring generation can be achieved within a short time period, and offers the opportunity for direct and quantitative assessment of the contributions of cells and cell-derived matrix (CDM) to vascular tissue structure and function.

This article outlines a versatile method to create cell-derived tissue rings by cellular self-assembly. Smooth muscle cells seeded into ring-shaped agarose wells aggregate and contract to form robust three-dimensional (3D) tissues within 7 days. Millimeter-scale tissue rings are conducive to mechanical testing and serve as building blocks for tissue assembly.

Each year, hundreds of thousands of patients undergo coronary artery bypass surgery in the United States.1 Approximately one third of these patients do ...

Ferromagnetic Bare Metal Stent for Endothelial Cell Capture and Retention

Rapid endothelialization of cardiovascular stents is needed to reduce stent thrombosis and to avoid anti-platelet therapy which can reduce bleeding risk. The feasibility of using magnetic forces to capture and retain endothelial outgrowth cells (EOC) labeled with super paramagnetic iron oxide nanoparticles (SPION) has been shown previously. But this technique requires the development of a mechanically functional stent from a magnetic and biocompatible material followed by in-vitro and in-vivo testing to prove rapid endothelialization. We developed a weakly ferromagnetic stent from 2205 duplex stainless steel using computer aided design (CAD) and its design was further refined using finite element analysis (FEA). The final design of the stent exhibited a principal strain below the fracture limit of the material during mechanical crimping and expansion. One hundred stents were manufactured and a subset of them was used for mechanical testing, retained magnetic field measurements, in-vitro cell capture studies, and in-vivo implantation studies. Ten stents were tested for deployment to verify if they sustained crimping and expansion cycle without failure. Another 10 stents were magnetized using a strong neodymium magnet and their retained magnetic field was measured. The stents showed that the retained magnetism was sufficient to capture SPION-labeled EOC in our in-vitro studies. SPION-labeled EOC capture and retention was verified in large animal models by implanting 1 magnetized stent and 1 non-magnetized control stent in each of 4 pigs. The stented arteries were explanted after 7 days and analyzed histologically. The weakly magnetic stents developed in this study were capable of attracting and retaining SPION-labeled endothelial cells which can promote rapid healing.

Our goals were to design, manufacture and test ferromagnetic stents for endothelial cell capture. Ten stents were tested for fracture and 10 more stents were tested for retained magnetism. Finally, 10 stents were tested in-vitro and 8 more stents were implanted in 4 pigs to show cell capture and retention.

Rapid endothelialization of cardiovascular stents is needed to reduce stent thrombosis and to avoid anti-platelet therapy which can reduce bleeding risk. ...

Training Persons with Spinal Cord Injury to Ambulate Using a Powered Exoskeleton

Powered exoskeletons have become available for overground ambulation in persons with paralyses due to spinal cord injury (SCI) who have intact upper extremity function and are able to maintain upright balance using forearm crutches. To ambulate in an exoskeleton, the user must acquire the ability to maintain balance while standing, sitting and appropriate weight shifting with each step. This can be a challenging task for those with deficits in sensation and proprioception in their lower extremities. This manuscript describes screening criteria and a training program developed at the James J. Peters VA Medical Center, Bronx, NY to teach users the skills needed to utilize these devices in institutional, home or community environments. Before training can begin, potential users are screened for appropriate range of motion of the hip, knee and ankle joints. Persons with SCI are at an increased risk of sustaining lower extremity fractures, even with minimal strain or trauma, therefore a bone mineral density assessment is performed to reduce the risk of fracture. Also, as part of screening, a physical examination is performed in order to identify additional health-related contraindications. 
Once the person has successfully passed all screening requirements, they are cleared to begin the training program. The device is properly adjusted to fit the user. A series of static and dynamic balance tasks are taught and performed by the user before learning to walk. The person is taught to ambulate in various environments ranging from indoor level surfaces to outdoors over uneven or changing surfaces. Once skilled enough to be a candidate for home use with the exoskeleton, the user is then required to designate a companion-walker who will train alongside them. Together, the pair must demonstrate the ability to perform various advanced tasks in order to be permitted to use the exoskeleton in their home/community environment.

Training a person with paralysis to ambulate using a powered exoskeleton may present challenges. The goals are to present the candidate selection criteria and the training procedures for exoskeletal-assisted walking and other mobility skills that can be progressed as the participant's skill level improves.

Powered exoskeletons have become available for overground ambulation in persons with paralyses due to spinal cord injury (SCI) who have intact upper ...

Biomechanical Characterization of Human Soft Tissues Using Indentation and Tensile Testing

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should mimic the human tissues they are aiming to replace; to provide the required anatomical shape, the materials must be able to sustain the mechanical forces they will experience when implanted at the defect site. Although the mechanical properties of tissue-engineered scaffolds are of great importance, many human tissues that undergo restoration with engineered materials have not been fully biomechanically characterized. Several compressive and tensile protocols are reported for evaluating materials, but with large variability it is difficult to compare results between studies. Further complicating the studies is the often destructive nature of mechanical testing. Whilst an understanding of tissue failure is important, it is also important to have knowledge of the elastic and viscoelastic properties under more physiological loading conditions.
This report aims to provide a minimally destructive protocol to evaluate the compressive and tensile properties of human soft tissues. As examples of this technique, the tensile testing of skin and the compressive testing of cartilage are described. These protocols can also be directly applied to synthetic materials to ensure that the mechanical properties are similar to the native tissue. Protocols to assess the mechanical properties of human native tissue will allow a benchmark by which to create suitable tissue-engineered substitutes.

Tissue biomechanics is important for maintaining cell shape and function and for determining phenotype. This report demonstrates non-destructive mechanical protocols for characterizing elastic and viscoelastic properties of human soft tissues, which can be directly applied to tissue-engineered substrates to allow a close matching of engineered materials to native tissue.

Regenerative medicine aims to engineer materials to replace or restore damaged or diseased organs. The mechanical properties of such materials should ...

An Experimental and Finite Element Protocol to Investigate the Transport of Neutral and Charged Solutes across Articular Cartilage

Osteoarthritis (OA) is a debilitating disease that is associated with degeneration of articular cartilage and subchondral bone. Degeneration of articular cartilage impairs its load-bearing function substantially as it experiences tremendous chemical degradation, i.e. proteoglycan loss and collagen fibril disruption. One promising way to investigate chemical damage mechanisms during OA is to expose the cartilage specimens to an external solute and monitor the diffusion of the molecules. The degree of cartilage damage (i.e. concentration and configuration of essential macromolecules) is associated with collisional energy loss of external solutes while moving across articular cartilage creates different diffusion characteristics compared to healthy cartilage. In this study, we introduce a protocol, which consists of several steps and is based on previously developed experimental micro-Computed Tomography (micro-CT) and finite element modeling. The transport of charged and uncharged iodinated molecules is first recorded using micro-CT, which is followed by applying biphasic-solute and multiphasic finite element models to obtain diffusion coefficients and fixed charge densities across cartilage zones.

We propose a protocol to investigate the transport of charged and uncharged molecules across articular cartilage with the aid of recently developed experimental and numerical methods.

Osteoarthritis (OA) is a debilitating disease that is associated with degeneration of articular cartilage and subchondral bone. Degeneration of articular ...

A Microfluidic Flow Chamber Model for Platelet Transfusion and Hemostasis Measures Platelet Deposition and Fibrin Formation in Real-time

Microfluidic models of hemostasis assess platelet function under conditions of hydrodynamic shear, but in the presence of anticoagulants, this analysis is restricted to platelet deposition only. The intricate relationship between Ca2+-dependent coagulation and platelet function requires careful and controlled recalcification of blood prior to analysis. Our setup uses a Y-shaped mixing channel, which supplies concentrated Ca2+/Mg2+ buffer to flowing blood just prior to perfusion, enabling rapid recalcification without sample stasis. A ten-fold difference in flow velocity between both reservoirs minimizes dilution. The recalcified blood is then perfused in a collagen-coated analysis chamber, and differential labeling permits real-time imaging of both platelet and fibrin deposition using fluorescence video microscopy. The system uses only commercially available tools, increasing the chances of standardization. Reconstitution of thrombocytopenic blood with platelets from banked concentrates furthermore models platelet transfusion, proving its use in this research domain. Exemplary data demonstrated that coagulation onset and fibrin deposition were linearly dependent on the platelet concentration, confirming the relationship between primary and secondary hemostasis in our model. In a timeframe of 16 perfusion min, contact activation did not take place, despite recalcification to normal Ca2+ and Mg2+ levels. When coagulation factor XIIa was inhibited by corn trypsin inhibitor, this time frame was even longer, indicating a considerable dynamic range in which the changes in the procoagulant nature of the platelets can be assessed. Co-immobilization of tissue factor with collagen significantly reduced the time to onset of coagulation, but not its rate. The option to study the tissue factor and/or the contact pathway increases the versatility and utility of the assay.

This paper describes an experimental model of hemostasis that simultaneously measures platelet function and coagulation. Platelet and fibrin fluorescence is measured in real-time, and platelet adhesion rate, coagulation rate, and onset of coagulation are determined. The model is used to determine platelet procoagulant properties under flow in concentrates for transfusion.

Microfluidic models of hemostasis assess platelet function under conditions of hydrodynamic shear, but in the presence of anticoagulants, this analysis is ...

Retroductal Nanoparticle Injection to the Murine Submandibular Gland

Two common goals of salivary gland therapeutics are prevention and cure of tissue dysfunction following either autoimmune or radiation injury. By locally delivering bioactive compounds to the salivary glands, greater tissue concentrations can be safely achieved versus systemic administration. Furthermore, off target tissue effects from extra-glandular accumulation of material can be dramatically reduced. In this regard, retroductal injection is a widely used method for investigating both salivary gland biology and pathophysiology. Retroductal administration of growth factors, primary cells, adenoviral vectors, and small molecule drugs has been shown to support gland function in the setting of injury. We have previously shown the efficacy of a retroductally injected nanoparticle-siRNA strategy to maintain gland function following irradiation. Here, a highly effective and reproducible method to administer nanomaterials to the murine submandibular gland through Wharton's duct is detailed (Figure 1). We describe accessing the oral cavity and outline the steps necessary to cannulate Wharton's duct, with further observations serving as quality checks throughout the procedure.

Local drug delivery to the submandibular glands is of interest in understanding salivary gland biology and for the development of novel therapeutics. We present an updated and detailed retroductal injection protocol, designed to improve delivery accuracy and experimental reproducibility. The application presented herein is the delivery of polymeric nanoparticles.

Two common goals of salivary gland therapeutics are prevention and cure of tissue dysfunction following either autoimmune or radiation injury. By locally ...

Seeding and Implantation of a Biosynthetic Tissue-engineered Tracheal Graft in a Mouse Model

Treatment options for congenital or secondary long segment tracheal defects have historically been limited due to an inability to replace functional tissue. Tissue engineering holds great promise as a potential solution with its ability to integrate cells and signaling molecules into a 3-dimensional scaffold. Recent work with tissue engineered tracheal grafts (TETGs) has seen some success but their translation has been limited by graft stenosis, graft collapse, and delayed epithelialization. In order to investigate the mechanisms driving these issues, we have developed a mouse model for tissue engineered tracheal graft implantation. TETGs were constructed using electrospun polymers polyethylene terephthalate (PET) and polyurethane (PU) in a mixture of PET and PU (20:80 percent weight). Scaffolds were then seeded using bone marrow mononuclear cells isolated from 6-8 week-old C57BL/6 mice by gradient centrifugation. Ten million cells per graft were seeded onto the lumen of the scaffold and allowed to incubate overnight before implantation between the third and seventh tracheal rings. These grafts were able to recapitulate the findings of stenosis and delayed epithelialization as demonstrated by histological analysis and lack of Keratin 5 and Keratin 14 basal epithelial cells on immunofluorescence. This model will serve as a tool for investigating cellular and molecular mechanisms involved in host remodeling.

Graft stenosis poses a critical obstacle in tissue engineered airway replacement. To investigate cellular mechanisms underlying stenosis, we utilize a murine model of tissue engineered tracheal replacement with seeded bone marrow mononuclear cells (BM-MNC). Here, we detail our protocol, including scaffold manufacturing, BM-MNC isolation, graft seeding, and implantation.

Treatment options for congenital or secondary long segment tracheal defects have historically been limited due to an inability to replace functional ...