Head Impact Biomechanics in Youth Hockey: Comparisons Across Playing Position, Event Types, and Impact Locations

The age at which young hockey players should safely body check is unknown. We sought to determine if playing position (defensemen vs. forwards), event type (practice vs. game), or head impact location (top vs. back vs. front vs. sides) had an effect on head impact biomechanics in youth hockey. A total of 52 Bantam (13–14 years old) and Midget (15–16 years old) ice hockey players wore accelerometer-instrumented helmets for two seasons. Biomechanical data were captured for 12,253 head impacts during 151 games and 137 practices. Random intercepts general mixed linear models were employed to analyze differences in linear acceleration, rotational acceleration, and HITsp by player position, event type, and head impact location. Head impacts sustained during games resulted in greater rotational acceleration and HITsp than those sustained during practices. No event type or playing position differences in linear acceleration were observed. Impacts to the top of the head resulted in greater linear acceleration, but lower rotational acceleration and HITsp, than impacts to back, front, or side of the head. Side head impacts yielded greater rotational acceleration and HITsp compared to the other head impact locations. Since linear and rotational accelerations were observed in all impacts, future hockey helmet design standards should include rotational acceleration limits in addition to the current linear acceleration standards.     

The Importance of the Scalp in Head Impact Kinematics

The best way to reduce the risk of head injury (up to 69% reduction) is to wear a helmet. In recent years, the improvement of helmet standard tests focused on reproducing realistic impact conditions and including the effect of rotational acceleration. However, less importance has been given to the development of a realistic headform. The goal of this work was to evaluate the role of scalp tissue in head impact kinematics; both with respect to its mechanical properties and with respect to its sliding properties. An EN960 and HIII headform were subjected to linear and oblique impacts, respectively, both with and without porcine scalp attached. Different speeds, impact locations and impact surfaces were tested. Standard linear drop tests (EN960) showed that the scalp reduced the impact energy by up to 68.7% (rear impact). Oblique head impact tests showed how the headform-anvil friction coefficient changes when the HIII is covered with scalp, affecting linear and rotational accelerations. Therefore, the scalp plays an important role in head impacts and it should be realistically represented in headforms used for impact tests and in numerical models of the human head.     

Validation of Concussion Risk Curves for Collegiate Football Players Derived from HITS Data

For several years, Virginia Tech and other schools have measured the frequency and severity of head impacts sustained by collegiate American football players in real time using the Head Impact Telemetry (HIT) System of helmet-mounted accelerometers. In this study, data from 37,128 head impacts collected at Virginia Tech during games from 2006 to 2010 were analyzed. Peak head acceleration exceeded 100 g in 516 impacts, and the Head Injury Criterion (HIC) exceeded 200 in 468 impacts. Four instrumented players in the dataset sustained a concussion. These data were used to develop risk curves for concussion as a function of peak head acceleration and HIC. The validity of this biomechanical approach was assessed using epidemiological data on concussion incidence from other sources. Two specific aspects of concussion incidence were addressed: the variation by player position, and the frequency of repeat concussions. The HIT System data indicated that linemen sustained the highest overall number of head impacts, while skill positions sustained a higher number of more severe head impacts (peak acceleration > 100 g or HIC > 200). When weighted using injury risk curves, the HIT System data predicted a higher incidence of concussion in skill positions compared to linemen at rates that were in strong agreement with the epidemiological literature (Pearson’s r = 0.72–0.87). The predicted rates of repeat concussions (21–39% over one season and 33–50% over five seasons) were somewhat higher than the ranges reported in the epidemiological literature. These analyses demonstrate that simple biomechanical parameters that can be measured by the HIT System possess a high level of power for predicting concussion.     

Brain Injury Prediction: Assessing the Combined Probability of Concussion Using Linear and Rotational Head Acceleration

Recent research has suggested possible long term effects due to repetitive concussions, highlighting the importance of developing methods to accurately quantify concussion risk. This study introduces a new injury metric, the combined probability of concussion, which computes the overall risk of concussion based on the peak linear and rotational accelerations experienced by the head during impact. The combined probability of concussion is unique in that it determines the likelihood of sustaining a concussion for a given impact, regardless of whether the injury would be reported or not. The risk curve was derived from data collected from instrumented football players (63,011 impacts including 37 concussions), which was adjusted to account for the underreporting of concussion. The predictive capability of this new metric is compared to that of single biomechanical parameters. The capabilities of these parameters to accurately predict concussion incidence were evaluated using two separate datasets: the Head Impact Telemetry System (HITS) data and National Football League (NFL) data collected from impact reconstructions using dummies (58 impacts including 25 concussions). Receiver operating characteristic curves were generated, and all parameters were significantly better at predicting injury than random guessing. The combined probability of concussion had the greatest area under the curve for all datasets. In the HITS dataset, the combined probability of concussion and linear acceleration were significantly better predictors of concussion than rotational acceleration alone, but not different from each other. In the NFL dataset, there were no significant differences between parameters. The combined probability of concussion is a valuable method to assess concussion risk in a laboratory setting for evaluating product safety.     

An Instrumented Mouthguard for Measuring Linear and Angular Head Impact Kinematics in American Football

The purpose of this study was to evaluate a novel instrumented mouthguard as a research device for measuring head impact kinematics. To evaluate kinematic accuracy, laboratory impact testing was performed at sites on the helmet and facemask for determining how closely instrumented mouthguard data matched data from an anthropomorphic test device. Laboratory testing results showed that peak linear acceleration (r ² = 0.96), peak angular acceleration (r ² = 0.89), and peak angular velocity (r ² = 0.98) measurements were highly correlated between the instrumented mouthguard and anthropomorphic test device. Normalized root-mean-square errors for impact time traces were 9.9 ± 4.4% for linear acceleration, 9.7 ± 7.0% for angular acceleration, and 10.4 ± 9.9% for angular velocity. This study demonstrates the potential of an instrumented mouthguard as a research tool for measuring in vivo impacts, which could help uncover the link between head impact kinematics and brain injury in American football.     

Rotational Head Kinematics in Football Impacts: An Injury Risk Function for Concussion

Recent research has suggested a possible link between sports-related concussions and neurodegenerative processes, highlighting the importance of developing methods to accurately quantify head impact tolerance. The use of kinematic parameters of the head to predict brain injury has been suggested because they are indicative of the inertial response of the brain. The objective of this study is to characterize the rotational kinematics of the head associated with concussive impacts using a large head acceleration dataset collected from human subjects. The helmets of 335 football players were instrumented with accelerometer arrays that measured head acceleration following head impacts sustained during play, resulting in data for 300,977 sub-concussive and 57 concussive head impacts. The average sub-concussive impact had a rotational acceleration of 1230 rad/s² and a rotational velocity of 5.5 rad/s, while the average concussive impact had a rotational acceleration of 5022 rad/s² and a rotational velocity of 22.3 rad/s. An injury risk curve was developed and a nominal injury value of 6383 rad/s² associated with 28.3 rad/s represents 50% risk of concussion. These data provide an increased understanding of the biomechanics associated with concussion and they provide critical insight into injury mechanisms, human tolerance to mechanical stimuli, and injury prevention techniques.     

Change in Size and Impact Performance of Football Helmets from the 1970s to 2010

Linear impactor tests were conducted on football helmets from the 1970s–1980s to complement recently reported tests on 1990s and 2010s helmets. Helmets were placed on the Hybrid III head with an array of accelerometers to determine translational and rotational acceleration. Impacts were at four sites on the helmet shell at 3.6–11.2 m/s. The four generations of helmets show a continuous improvement in response from bare head impacts in terms of Head Injury Criterion (HIC), peak head acceleration and peak rotational acceleration. Helmets of 2010s weigh 1.95 ± 0.2 kg and are 2.7 times heavier than 1970s designs. They are also 4.3 cm longer, 7.6 cm higher, and 4.9 cm wider. The extra size and weight allow the use of energy absorbing padding that lowers forces in helmet impacts. For frontal impacts at 7.4 m/s, the four best performing 2010s helmets have HIC of 148 ± 23 compared to 179 ± 42 for the 1990s baseline, 231 ± 27 for the 1980s, 253 ± 22 for the 1970s helmets, and 354 ± 3 for the bare head. The additional size and padding of the best 2010s helmets provide superior attenuation of impact forces in normal play and in conditions associated with concussion than helmets of the 1970s–1990s.     

Impact Performance of Modern Football Helmets

Linear impact tests were conducted on 17 modern football helmets. The helmets were placed on the Hybrid III head with the neck attached to a sliding table. The head was instrumented with an array of 3-2-2-2 accelerometers to determine translational acceleration, rotational acceleration, and HIC. Twenty-three (23) different impacts were conducted on four identical helmets of each model at eight sites on the shell and facemask, four speeds (5.5, 7.4, 9.3, and 11.2 m/s) and two temperatures (22.2 and 37.8 °C). There were 1,850 tests in total; 276 established the 1990s helmet performance (baseline) and 1,564 were on the 17 different helmet models. Differences from the 1990s baseline were evaluated using the Student t test (p < 0.05 as significant). Four of the helmets had significantly lower HICs and head accelerations than the 1990s baseline with average reductions of 14.6–21.9% in HIC, 7.3–14.0% in translational acceleration, and 8.4–15.9% in rotational acceleration. Four other helmets showed some improvements. Eight were not statistically different from the 1990s baseline and one had significantly poorer performance. Of the 17 helmet models, four provided a significant reduction in head responses compared to 1990s helmets.     

Football Helmet Drop Tests on Different Fields Using an Instrumented Hybrid III Head

An instrumented Hybrid III head was placed in a Schutt ION 4D football helmet and dropped on different turfs to study field types and temperature on head responses. The head was dropped 0.91 and 1.83 m giving impacts of 4.2 and 6.0 m/s on nine different football fields (natural, Astroplay, Fieldturf, or Gameday turfs) at turf temperatures of −2.7 to 23.9 °C. Six repeat tests were conducted for each surface at 0.3 m (1′) intervals. The Hybrid III was instrumented with triaxial accelerometers to determine head responses for the different playing surfaces. For the 0.91-m drops, peak head acceleration varied from 63.3 to 117.1 g and HIC₁₅ from 195 to 478 with the different playing surfaces. The lowest response was with Astroplay, followed by the engineered natural turf. Gameday and Fieldturf involved higher responses. The differences between surfaces decreased in the 1.83 m tests. The cold weather testing involved higher accelerations, HIC₁₅ and delta V for each surface. The helmet drop test used in this study provides a simple and convenient means of evaluating the compliance and energy absorption of football playing surfaces. The type and temperature of the playing surface influence head responses.     

Head Impact Exposure in Youth Football: High School Ages 14 to 18 Years and Cumulative Impact Analysis

Sports-related concussion is the most common athletic head injury with football having the highest rate among high school athletes. Traditionally, research on the biomechanics of football-related head impact has been focused at the collegiate level. Less research has been performed at the high school level, despite the incidence of concussion among high school football players. The objective of this study is to twofold: to quantify the head impact exposure in high school football, and to develop a cumulative impact analysis method. Head impact exposure was measured by instrumenting the helmets of 40 high school football players with helmet mounted accelerometer arrays to measure linear and rotational acceleration. A total of 16,502 head impacts were collected over the course of the season. Biomechanical data were analyzed by team and by player. The median impact for each player ranged from 15.2 to 27.0 g with an average value of 21.7 (±2.4) g. The 95th percentile impact for each player ranged from 38.8 to 72.9 g with an average value of 56.4 (±10.5) g. Next, an impact exposure metric utilizing concussion injury risk curves was created to quantify cumulative exposure for each participating player over the course of the season. Impacts were weighted according to the associated risk due to linear acceleration and rotational acceleration alone, as well as the combined probability (CP) of injury associated with both. These risks were summed over the course of a season to generate risk weighted cumulative exposure. The impact frequency was found to be greater during games compared to practices with an average number of impacts per session of 15.5 and 9.4, respectively. However, the median cumulative risk weighted exposure based on combined probability was found to be greater for practices vs. games. These data will provide a metric that may be used to better understand the cumulative effects of repetitive head impacts, injury mechanisms, and head impact exposure of athletes in football.     

Effect of Mouthguards on Head Responses and Mandible Forces in Football Helmet Impacts

The potential for mouthguards to change the risk of concussion was studied in football helmet impacts. The Hybrid III head was modified with an articulating mandible, dentition, and compliant temporomandibular joints (TMJ). It was instrumented for triaxial head acceleration and triaxial force at the TMJs and upper dentition. Mandible force and displacement were validated against cadaver impacts to the chin. In phase 1, one of five mouthguards significantly lowered HIC in 6.7 m/s impacts (p = 0.025) from the no mouthguard condition but not in 9.5 m/s tests. In phase 2, eight mouthguards increased HIC from +1 to +17% in facemask impacts that loaded the chinstraps and mandible; one was statistically higher (p = 0.018). Peak head acceleration was +1 to +15% higher with six mouthguards and 2–3% lower with two others. The differences were not statistically significant. Five of eight mouthguards significantly reduced forces on the upper dentition by 40.8–63.9%. Mouthguards tested in this study with the Hybrid III articulating mandible lowered forces on the dentition and TMJ, but generally did not influence HIC or concussion risks.     

Dynamic Response and Residual Helmet Liner Crush Using Cadaver Heads and Standard Headforms

Biomechanical headforms are used for helmet certification testing and reconstructing helmeted head impacts; however, their biofidelity and direct applicability to human head and helmet responses remain unclear. Dynamic responses of cadaver heads and three headforms and residual foam liner deformations were compared during motorcycle helmet impacts. Instrumented, helmeted heads/headforms were dropped onto the forehead region against an instrumented flat anvil at 75, 150, and 195 J. Helmets were CT scanned to quantify maximum liner crush depth and crush volume. General linear models were used to quantify the effect of head type and impact energy on linear acceleration, head injury criterion (HIC), force, maximum liner crush depth, and liner crush volume and regression models were used to quantify the relationship between acceleration and both maximum crush depth and crush volume. The cadaver heads generated larger peak accelerations than all three headforms, larger HICs than the International Organization for Standardization (ISO), larger forces than the Hybrid III and ISO, larger maximum crush depth than the ISO, and larger crush volumes than the DOT. These significant differences between the cadaver heads and headforms need to be accounted for when attempting to estimate an impact exposure using a helmet’s residual crush depth or volume.     

Dynamic Response Due to Behind Helmet Blunt Trauma Measured with a Human Head Surrogate

A Human Head Surrogate has been developed for use in behind helmet blunt trauma experiments. This human head surrogate fills the void between Post-Mortem Human Subject testing (with biofidelity but handling restrictions) and commercial ballistic head forms (with no biofidelity but ease of use). This unique human head surrogate is based on refreshed human craniums and surrogate materials representing human head soft tissues such as the skin, dura, and brain. A methodology for refreshing the craniums is developed and verified through material testing. A test methodology utilizing these unique human head surrogates is also developed and then demonstrated in a series of experiments in which non-perforating ballistic impact of combat helmets is performed with and without supplemental ceramic appliques for protecting against larger caliber threats. Sensors embedded in the human head surrogates allow for direct measurement of intracranial pressure, cranial strain, and head and helmet acceleration. Over seventy (70) fully instrumented experiments have been executed using this unique surrogate. Examples of the data collected are presented. Based on these series of tests, the Southwest Research Institute (SwRI) Human Head Surrogate has demonstrated great potential for providing insights in to injury mechanics resulting from non-perforating ballistic impact on combat helmets, and directly supports behind helmet blunt trauma studies.     

Individual Impact Magnitude vs. Cumulative Magnitude for Estimating Concussion Odds

Helmeted impact devices have allowed researchers to investigate the biomechanics of head impacts in vivo. While increased impact magnitude has been associated with greater concussion risk, a definitive concussive threshold has not been established. It is likely that concussion risk is not determined by a single impact itself, but a host of predisposing factors. These factors may include genetics, fatigue, and/or prior head impact exposure. The objective of the current paper is to investigate the association between cumulative head impact magnitude and concussion risk. It is hypothesized that increased cumulative magnitudes will be associated with greater concussion risk. This retrospective analysis included participants that were recruited from regional high-schools in Illinois and Michigan from 2007 to 2014 as part of an ongoing study on concussion biomechanics. Across seven seasons, 185 high school football athletes were instrumented with the Head Impact Telemetry system. Out of 185 athletes, 31 (17%) sustained a concussion, with two athletes sustaining two concussions over the study period, yielding 33 concussive events. The system recorded 78,204 impacts for all concussed players. Linear acceleration, rotational acceleration, and head impact telemetry severity profile (HITsp) magnitudes were summed within five timeframes: the day of injury, three days prior to injury, seven days prior to injury, 30 days prior to injury, and prior in-season exposure. Logistic regressions were modeled to explain concussive events based on the singular linear acceleration, rotational acceleration, and HITsp event along with the calculated summations over time. Linear acceleration, rotational acceleration, and HITsp all produced significant models estimating concussion (p < 0.05). The strongest estimators of a concussive impact were the linear acceleration (OR = 1.040, p < 0.05), rotational acceleration (OR = 1.001, p < 0.05), and HITsp (OR = 1.003, p < 0.05) for the singular impact rather than any of the cumulative magnitude calculations. Moreover, no cumulative count measure was significant for linear or rotational acceleration. Results from this investigation support the growing literature indicating cumulative magnitude is not related to concussion likelihood. Cumulative magnitude is a simplistic measure of the total exposure sustained by a player over a given period. However, this measure is limited as it assumes the brain is a static structure unable to undergo self-repair. Future research should consider how biological recovery between impacts may influence concussion risk.     

Development of a Multimodal Blast Sensor for Measurement of Head Impact and Over-pressurization Exposure

It is estimated that 10–20% of United States soldiers returning from Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF) have suffered at least one instance of blast-induced traumatic brain injury (bTBI) with many reporting persistent symptomology and long-term effects. This variation in blast response may be related to the complexity of blast waves and the many mechanisms of injury, including over-pressurization due to the shock wave and potential for blunt impacts to the head from shrapnel or from other indirect impacts (e.g., building, ground, and vehicle). To help differentiate the effects of primary, secondary, and tertiary effects of blast, a custom sensor was developed to simultaneously measure over-pressurization and blunt impact. Moreover, a custom, complementary filter was designed to differentiate the measurements of blunt (low-frequency bandwidth) from over-pressurization (high-frequency bandwidth). The custom sensor was evaluated in the laboratory using a shock tube to simulate shock waves and a drop fixture to simulate head impacts. Both bare sensors and sensor embedded within an ACH helmet coupon were compared to laboratory reference transducers under multiple loading conditions (n = 5) and trials at each condition (n = 3). For all comparative measures, peak magnitude, peak impulse, and cross-correlation measures, R ² values, were greater than 0.900 indicating excellent agreement of peak measurements and time-series comparisons with laboratory measures.     

Head Impact Exposure in Youth Football: Elementary School Ages 9–12 Years and the Effect of Practice Structure

Head impact exposure in youth football has not been well-documented, despite children under the age of 14 accounting for 70% of all football players in the United States. The objective of this study was to quantify the head impact exposure of youth football players, age 9–12, for all practices and games over the course of single season. A total of 50 players (age = 11.0 ± 1.1 years) on three teams were equipped with helmet mounted accelerometer arrays, which monitored each impact players sustained during practices and games. During the season, 11,978 impacts were recorded for this age group. Players averaged 240 ± 147 impacts for the season with linear and rotational 95th percentile magnitudes of 43 ± 7 g and 2034 ± 361 rad/s². Overall, practice and game sessions involved similar impact frequencies and magnitudes. One of the three teams however, had substantially fewer impacts per practice and lower 95th percentile magnitudes in practices due to a concerted effort to limit contact in practices. The same team also participated in fewer practices, further reducing the number of impacts each player experienced in practice. Head impact exposures in games showed no statistical difference. While the acceleration magnitudes among 9–12 year old players tended to be lower than those reported for older players, some recorded high magnitude impacts were similar to those seen at the high school and college level. Head impact exposure in youth football may be appreciably reduced by limiting contact in practices. Further research is required to assess whether such a reduction in head impact exposure will result in a reduction in concussion incidence.     

Head impact exposure in youth football

The head impact exposure for athletes involved in football at the college and high school levels has been well documented; however, the head impact exposure of the youth population involved with football has yet to be investigated, despite its dramatically larger population. The objective of this study was to investigate the head impact exposure in youth football. Impacts were monitored using a custom 12 accelerometer array equipped inside the helmets of seven players aged 7–8 years old during each game and practice for an entire season. A total of 748 impacts were collected from the 7 participating players during the season, with an average of 107 impacts per player. Linear accelerations ranged from 10 to 100 g, and the rotational accelerations ranged from 52 to 7694 rad/s². The majority of the high level impacts occurred during practices, with 29 of the 38 impacts above 40 g occurring in practices. Although less frequent, youth football can produce high head accelerations in the range of concussion causing impacts measured in adults. In order to minimize these most severe head impacts, youth football practices should be modified to eliminate high impact drills that do not replicate the game situations.     

The Relationship Between Subconcussive Impacts and Concussion History on Clinical Measures of Neurologic Function in Collegiate Football Players

Concussions sustained during college and professional football careers have been associated with both acute and chronic neurologic impairment. The contribution of subconcussive impacts to this impairment has not been adequately studied. Therefore, we investigated the relationship between subconcussive impacts and concussion history on clinical measures of neurologic function. Forty-six collegiate football players completed five clinical measures of neurologic function commonly employed in the evaluation of concussion before and after a single season. These tests included the Automated Neuropsychological Assessment Metrics, Sensory Organization Test, Standardized Assessment of Concussion, Balance Error Scoring System, and Graded Symptom Checklist. The Head Impact Telemetry (HIT) System recorded head impact data including the frequency, magnitude, and location of impacts. College football players sustain approximately 1,000 subconcussive impacts to the head over the course of a season, but for the most part, do not demonstrate any clinically meaningful changes from preseason to postseason on measures of neurologic function. Changes in performance were mostly independent of prior concussion history, and the total number, magnitude and location of sustained impacts over one season as observed R ² values ranged between 0.30 and 0.35. Repetitive subconcussive head impacts over a single season do not appear to result in short-term neurologic impairment, but these relationships should be further investigated for a potential dose–response over a player’s career.     

A Headform for Testing Helmet and Mouthguard Sensors that Measure Head Impact Severity in Football Players

A headform is needed to validate and compare helmet- and mouthguard-based sensors that measure the severity and direction of football head impacts. Our goal was to quantify the dynamic response of a mandibular load-sensing headform (MLSH) and to compare its performance and repeatability to an unmodified Hybrid III headform. Linear impactors in two independent laboratories were used to strike each headform at six locations at 5.5 m/s and at two locations at 3.6 and 7.4 m/s. Impact severity was quantified using peak linear acceleration (PLA) and peak angular acceleration (PAA), and direction was quantified using the azimuth and elevation of the PLA. Repeatability was quantified using coefficients of variation (COV) and standard deviations (SD). Across all impacts, PLA was 1.6 ± 1.8 g higher in the MLSH than in the Hybrid III (p = 0.002), but there were no differences in PAA (p = 0.25), azimuth (p = 0.43) and elevation (p = 0.11). Both headforms exhibited excellent or acceptable repeatability for PLA (HIII:COV = 2.1 ± 0.8%, MLSH:COV = 2.0 ± 1.2%, p = 0.98), but site-specific repeatability ranging from excellent to poor for PAA (HIII:COV = 7.2 ± 4.0%, MLSH:COV = 8.3 ± 5.8%, p = 0.58). Direction SD were generally <1° and did not vary between headforms. Overall, both headforms are similarly suitable for validating PLA in sensors that measure head impact severity in football players, however their utility for validating sensor PAA values varies with impact location.