Validation of a Custom Instrumented Retainer Form Factor for Measuring Linear and Angular Head Impact Kinematics.

USA Football established five levels-of-contact to guide the intensity of high school football practices. The objective of this study was to examine head impact frequency and magnitude by levels-of-contact to determine which drills had the greatest head impact exposure. Our primary hypothesis was that there would be an incremental increase in season-long head impact exposure between levels-of-contact: air<bags<control<thud<live. This observational study included 24 high-school football players during all 46 practices, 1 scrimmage, 9 junior varsity and 10 varsity games in the 2019 season. Players wore a sensor-installed mouthguard that monitored head impact frequency, peak linear acceleration (PLA), and rotational acceleration (PRA). Practice/game drills were filmed and categorized into five levels-of-contact (air, bags, control, thud, live), and head impact data were assigned into one of five levels-of-contact. Player position was categorized into lineman, hybrid, and skill. A total of 6016 head impacts were recorded during 5 levels-of-contact throughout the season. In the overall sample, total number of impacts, sum of PLA, and PRA per player increased in a near incremental manner (air<bags<control = thud<live), where live drills had significantly higher cumulative frequency (113.7±17.8 hits/player) and magnitude [2,657.6±432.0 g (PLA), and 233.9 ± 40.1 krad/s2 (PRA)] than any other levels-of-contact, whereas air drills showed the lowest cumulative frequency (7.7±1.9 hits/player) and magnitude [176.9±42.5 g (PLA), PRA 16.7±4.2 krad/s2 (PRA)]. There was no significant position group difference in cumulative head impact frequency and magnitude in a season. Although there was no difference in average head impact magnitude across five levels-of-contact and by position group PLA (18.2–23.2g) and PRA (1.6–2.3krad/s2) per impact], high magnitude (60-100g and >100g) head impacts were more frequently observed during live and thud drills. Level-of-contact influences cumulative head impact frequency and magnitude in high-school football, with players incurring frequent, high magnitude head impacts during live, thud, and control. It is important to consider level-of-contact to refine clinical exposure guidelines to minimize head impact burden in high-school football.

Hybrid III anthropomorphic test device (ATD) response to head impacts and potential implications for athletic headgear testing

With the concern of concussion risk and repetitive head impacts in youth football, organizations have adopted rules that limit contact during practice. However, rule changes are not ubiquitous among organizations and are challenging to monitor and enforce. Ultimately, football practice activities are determined by coaches, but it is unknown whether providing objective data to coaches relating activities to their athletes' head impact exposure (HIE) would alter practice structure or help reduce HIE. This study evaluated the effect of coach awareness of HIE on practice structure over time. Head impact data from three intervention (56 players) and three control (38 players) teams were collected over two youth football seasons. Athletes were instrumented with the Head Impact Telemetry (HIT) System and time-synchronized video was recorded for practices and games. Impact frequencies and head accelerations were compiled into weekly HIE practice and game reports and shared with the head coach of each intervention team. Time per drill, impact rate, and impact magnitude were compared across three time frames (pre-season, mid-season, and late-season) using generalized linear models. Control teams had higher impact rates than intervention teams in all drills across time frames. Among all teams, 95th percentile linear and rotational accelerations were highest during mid-season. Among intervention teams, more time was spent on scrimmage and skill development from pre-season to late-season, with less time spent on tackling. This study suggests that receiving objective data informing HIE in practice may contribute to changes in practice structure and help inform intervention efforts to improve head impact safety in football.

Background: There is growing fear among healthcare professionals and parents regarding youth tackle football, likely due to highly publicized concerns about potential long-term physical and cognitive health of professional football players. Parents and advocacy groups are pushing for state legislation to ban youth tackle football in favor of flag football to avoid repetitive head impacts that are potentially associated with late-life cognitive deficits. Although the head impact burden experienced during flag football is likely lower than tackle, no research has compared head impact exposure between youth tackle and flag football. Therefore, our purpose was to examine head impact exposure and magnitudes between youth tackle and flag football players. Methods: Twenty-seven tackle (age=11.0±1.5y, height=145.8±11.9 cm, mass=45.0±14.9 kg) and 29 flag football players (age=8.6±1.1y, height=133.9±8.4 cm, mass=33.9±9.5 kg) were enrolled in this prospective cohort study. Participants were fitted with head impact sensors (Triax Sim-G) worn throughout the entire 2017 season that recorded impact frequency and magnitude (linear [g] and rotational acceleration [rad/s2]). Athlete exposure was defined as one player participating in one session. Impact rates (IR) were calculated as impacts per one athlete exposure. Game, practice, and combined IR were compared between groups using impact rate ratios (IRR). IRR with 95% confidence intervals (CI) not containing 1.0 were considered statistically significant. Acceleration values were binned into low- and high-magnitude categories (linear split at 40 g, rotational split at 4,600rad/s2). Magnitude category frequencies were compared between groups using Chi-square test of association (p&lt;0.05), and 90th percentile acceleration values are presented. Results: One-thousand nine-hundred and eight tackle (735 game, 1173 practice; 70.66 impacts/player) and 169 flag (101 game, 68 practice; 5.83 impacts/player) football head impacts were recorded. Tackle players experienced a higher impact rate during games versus practices (IRR=1.41; 95%CI:1.29 -1.55) while flag players experienced a lower impact rate (IRR=0.60; 95%CI:0.44-0.81). Practice and game head impacts combined resulted in tackle players (IR=3.06) accruing 4.61 times the impact rate (95%CI:3.94-5.40) of flag players (IR=0.66). Tackle players sustained a significantly greater head impact rate than flag players during games (tackle IR=3.83, flag IR=0.55; IRR=6.90; 95%CI:5.60-8.49) and practices (tackle IR=2.72, flag IR=0.93; IRR=2.91; 95%CI:2.28-3.72). Tackle 90th percentile linear acceleration was 53.32 g (median=32.50 g) and flag was 53.32 g (median=32.65 g). Tackle 90th percentile rotational acceleration was 7,000 rad/s2 (median=3,200rad/s2) while flag was 8,300 rad/s2 (median=4,100rad/s2). Tackle experienced a significantly higher frequency of low-magnitude rotational acceleration impacts (71.6% vs. 57.4%) and lower frequency of high-magnitude impacts than flag (28.4% vs 42.6%;?2=15.15, p&lt;0.001). There were no significant associations for linear acceleration (p=0.75). Conclusions/Significance: Our results indicate youth flag football head impact rates are 82%-88% lower compared to tackle. Contrary to general belief, youth flag football players experienced numerous head impacts with a greater tendency for high-magnitude rotational acceleration head impacts. Although fewer head impacts occur during youth flag football, parents and coaches should be aware that head impacts do occur during practices and games. Whether high-magnitude or high-frequency head impacts influence long-term health remains unknown. Our findings provide novel evidence into the head impact exposure occurring during youth tackle and flag football. Longitudinal studies examining head impact biomechanics and advanced neuroimaging in youth tackle and flag football players nationwide is warranted to ensure long term cognitive health.

Biomechanical data collected from head impacts in football have been used to characterize exposure and predict injury risk. This study sought to specifically quantify the factors that contribute towards player head impact exposure in college football practices. All players included in this study were outfitted with football helmets instrumented with accelerometer arrays (Head Impact Telemetry System). Head impact exposure was defined by the number of head impacts each player experienced in practice, the number of practice head impacts normalized by the number of practice sessions (practice head impact rate), and the 95th percentile linear and rotational resultant head impact accelerations. Practice head impact rate was observed to vary significantly with player position (p < 0.0001; η2 = 0.46), team (p = 0.0016; η2 = 0.03), and the number of game impacts (p < 0.0001; η2 = 0.03), which served as a correlate for player ability. Even after controlling for practice participation, player position, team, and ability, differences between individuals accounted for 48% of the variance in head impact exposure in practice. This work demonstrates the importance of considering head impact exposure on a subject-specific basis rather than estimating head impact exposure from aggregate data.

Proper evaluation of ski helmet designs and safety standards should rely on head impact conditions involved in skiing and snowboarding head injuries. To study these impacts, main crash scenarios involving head injuries are numerically replicated. Multibody models of skiers and snowboarders were developed to investigate five common crash scenarios involved in traumatic brain injury: forward and sideways skiing falls, snowboarding backward falls, collisions between users and collisions with obstacles. For each scenario, the influence of crash conditions on head impact (location, speed, linear and rotational accelerations) and risk of injury are evaluated. Crash conditions were initial velocity, user height, position and approach angle, slope steepness, obstacles, and snow stiffness. One thousand one hundred forty-nine crashes were simulated and three significant levels of impact conditions were discriminated over the investigated crash scenarios: 1) the smallest normal-to-slope impact velocities (6 km·h; 22 km·h) and peak linear accelerations (42g; 75g) were obtained during forward and sideways skiing falls; 2) snowboarding backward falls and collisions between users were associated with high normal-to-surface impact velocities (26 km·h; 32 km·h) and head accelerations (80g; 149g) above one published threshold for mild traumatic brain injury but below the pass/fail criteria of helmet standard tests; 3) collisions with obstacles were associated with high normal-to-surface impact velocities (19 km·h; 35 km·h) and the highest head accelerations (626g; 1885g). Current impact conditions of helmet standard evaluations consistently replicate collisions with obstacles, but need to be revised to better reflect other significant crash scenarios leading to traumatic brain injury.

Effects of purposeful soccer heading on circulating small extracellular vesicle concentration and cargo

Following sport-related concussions, early head impact exposure and premature return to sport are known to increase the risk of repeat concussion in football athletes, yet athletes' true post-injury head impact exposure profiles (i.e., characteristics of recorded head impacts over a given time period) and biomechanical progression have not been explored. Accordingly, this study explored how head impact exposure in American college football athletes was altered during their return to sport from concussion, particularly within the same athletic season. This analysis compared daily volume of head impacts following concussion with pre-injury levels using head impact exposure profiles of 52 concussed collegiate football athletes from six NCAA Division I programs, and further compared these athletes to team- and position-matched controls to minimize season- or team-related factors. In addition, this study provided an analysis of the possible association between duration of recovery and change in head impact exposure following concussion using continuous linear regression. When comparing to pre-injury levels, 75% of concussed athletes reduced their head impact exposure in their immediate return to sport, whereas over 40% of concussed athletes did not reach their pre-injury level of head impact exposure at any point during the remainder of the concussion season segment. Furthermore, concussed athletes significantly decreased their head impact exposure over their immediate return-to-sport period when compared with team- and position-matched healthy, nonconcussed athletes over the same time period. Finally, longer postconcussion recovery times were associated with larger decreases in head impact exposure after return to sport. This study provides evidence for a shift in head impact exposure after returning from concussion, seen most strongly in the immediate days after return to sport. These findings align with the recent shift toward more conservative postconcussion management seen across multiple sports and playing levels.

Head impact exposure (HIE) (i.e., magnitude and frequency of impacts) can vary considerably among individuals within a single football team. To better understand individual-specific factors that may explain variation in head impact biomechanics, this study aimed to evaluate the relationship between physical performance measures and HIE metrics in youth football players. Head impact data were collected from youth football players using the Head Impact Telemetry System. Head impact exposure was quantified in terms of impact frequency, linear and rotational head acceleration, and risk-weighted cumulative exposure metrics (RWELinear, RWERotational, and RWECP). Study participants completed four physical performance tests: vertical jump, shuttle run, three-cone, and 40-yard sprint. The relationships between performance measures, and HIE metrics were evaluated using linear regression analyses. A total of 51 youth football athletes (ages, 9-13 yr) completed performance testing and received combined 13,770 head impacts measured with the Head Impact Telemetry System for a full season. All performance measures were significantly correlated with total number of impacts in a season, RWELinear-Season, and all RWE-Game metrics. The strongest relationships were between 40-yard sprint speed and all RWE-Game metrics (all P ≤ 0.0001 and partial R > 0.3). The only significant relationships among HIE metrics in practice were between shuttle run speed and total practice impacts and RWELinear-Practices, 40 yard sprint speed and total number of practice impacts, and three-cone speed and 95th percentile number of impacts/practice. Generally, higher vertical jump height and faster times in speed and agility drills were associated with higher HIE, especially in games. Physical performance explained less variation in HIE in practices, where drills and other factors, such as coaching style, may have a larger influence on HIE.

This study examined HIE of middle school football players over multiple seasons. Head impact exposure was evaluated in 103 football players (11-14 yr) who participated in a community-based youth tackle football program, up to 2 yr, with the same coaching staff over eight consecutive seasons (2012-2019). Head impact exposure was assessed using the Head Impact Telemetry System. Median of individual mean head impacts per session (HIPS) and median of individual 50th and 95th percentile head impact magnitudes were compared across seasons. There were 33,519 head impacts measured throughout the study. Median HIPS for all sessions decreased every year, with a significant reduction from 2012 to 2019 (11.1 vs 2.3 HIPS; P < 0.05). Median game HIPS were significantly reduced in 2019 compared with 2012-14 (5.00 vs 16.30-17.75 HIPS; P < 0.05). Median practice HIPS were reduced by 81.3%, whereas median game HIPS were reduced by 69.3%. Median 50th and 95th percentile linear and rotational acceleration were lower in 2019 compared with some earlier years but remained unchanged during games. Head impacts incurred by youth football players decreased substantially over eight seasons, with players in the final year sustaining approximately one fifth the HIPS as players experienced during the first year. The most prominent decline occurred in practices, although players also had much fewer head impacts in games. These results suggest that coaches' and/or players' behavior can be modified to greatly reduce the head impact burden in youth football.

A pilot study was performed to measure head impact accelerations in collegiate men’s ice hockey during the 2005–2007 seasons using helmets instrumented with Head Impact Telemetry System technology to monitor and record linear head accelerations and impact locations in situ. The objectives of this study were (1) to quantify the relationship between resultant peak linear head acceleration and impact location for in situ head impacts in collegiate men’s ice hockey, (2) to quantify the frequency and severity of impacts to the facemask, and (3) to determine if in situ impacts occurred such that the peak resultant linear head acceleration was higher than the peak resultant linear headform acceleration from a 40-in. linear drop (as in ASTM F1045–99) on the same helmet at a similar impact location. Voluntary participants (n=5 and 7 for years 1 and 2, respectively) wore instrumented helmets which monitored head impact accelerations sustained by each player during all games and practices. Head impact data were grouped by impact location into five bins representing top, back, side, forehead, and facemask. Forehead impacts represented impacts to the helmet shell as distinguished from facemask impacts. Additionally, a sample instrumented helmet was impacted in the laboratory at forehead, side, rear, and top impact locations (40-in. drop, three trials per location, test setup as specified in ASTM F1045-99). The mean peak resultant linear headform acceleration for each impact location was determined for analysis. Of the 4,393 recorded head impacts, 33.2 % were to the back of the helmet. This percentage increased to 59.2 % for impacts above 70 g. Facemask impacts accounted for 12.2 % of all impacts but only 2.4 % of impacts above 70 g. Over two seasons, five in situ impacts occurred such that the peak resultant linear head acceleration was greater than the mean peak resultant linear headform acceleration for a corresponding impact location in the laboratory. This study found that the most common impact location in ice hockey, particularly for impacts with higher peak linear accelerations, was the back of the head and demonstrated that facemask impacts were typically of a lower magnitude. The five impacts or ∼0.4 per player/season that exceeded the peak linear acceleration associated with 40-in. laboratory drops suggested that the impact energy specified in ASTM F1045 may not reflect the highest energy impacts seen in situ.

Cumulative exposure to head impacts during contact sports can elicit potentially deleterious brain white matter alterations in young athletes. Head impact exposure is commonly quantified using wearable sensors; however, these sensors tend to overestimate the number of true head impacts that occur and may obfuscate potential relationships with longitudinal brain changes. The purpose of this study was to examine whether data-driven filtering of head impact exposure using machine learning classification could produce more accurate quantification of exposure and whether this would reveal more pronounced relationships with longitudinal brain changes. Season-long head impact exposure was recorded for 22 female high school soccer athletes and filtered using three methods-threshold-based, heuristic filtering, and machine learning (ML) classification. The accuracy of each method was determined using simultaneous video recording of a subset of the sensor-recorded impacts, which was used to confirm which sensor-recorded impacts corresponded with true head impacts and the ability of each method to detect the true impacts. Each filtered dataset was then associated with the athletes' pre- and post-season MRI brain scans to reveal longitudinal white matter changes. The threshold-based, heuristic, and ML approaches achieved 22.0% accuracy, 44.6%, and 83.5% accuracy, respectively. ML classification also revealed significant longitudinal brain white matter changes, with negative relationships observed between head impact exposure and reductions in mean and axial diffusivity and a positive relationship observed between exposure and fractional anisotropy (all p < 0.05).

Contact sport athletes are exposed to a unique environment where they sustain repeated head impacts throughout the season and can sustain hundreds of head impacts over a few months. Accordingly, recent studies outlined the role that head impact exposure (HIE) has in concussion biomechanics and in the development of cognitive and brain-based changes. Those studies focused on time-bound effects by quantifying exposure leading up to the concussion, or cognitive changes after a season in which athletes had high HIE. However, HIE may have a more prolonged effect. This study identified associations between HIE and concussion incidence during different periods of the college football fall season. This study included 1120 athlete seasons from six National Collegiate Athletic Association Division I football programs across 5 yr. Athletes were instrumented with the Head Impact Telemetry System to record daily HIE. The analysis quantified associations of preseason/regular season/total season concussion incidence with HIE during those periods. Strong associations were identified between HIE and concussion incidence during different periods of the season. Preseason HIE was associated with preseason and total season concussion incidence, and total season HIE was associated with total season concussion incidence. These findings demonstrate a prolonged effect of HIE on concussion risk, wherein elevated preseason HIE was associated with higher concussion risk both during the preseason and throughout the entire fall season. This investigation is the first to provide evidence supporting the hypothesis of a relationship between elevated HIE during the college football preseason and a sustained decreased tolerance for concussion throughout that season.

The objective of this research was to characterize head impacts with a validated mouthpiece sensor in competitive youth female soccer players during a single season with a validated mouthpiece sensor. Participants included 14 youth female soccer athletes across 2 club-level teams at different age levels (team 1, ages 12-13y; team 2, ages 14-15y). Head impact and time-synchronized video data were collected for 66 practices and games. Video data were reviewed to characterize the type and frequency of contact experienced by each athlete. A total of 2216 contact scenarios were observed; heading the ball (n = 681, 30.7%) was most common. Other observed contact scenarios included collisions, dives, falls, and unintentional ball contact. Team 1 experienced a higher rate of headers per player per hour of play than team 2, while team 2 experienced a higher rate of collisions and dives. A total of 935 video-verified contact scenarios were concurrent with recorded head kinematics. While headers resulted in a maximum linear acceleration of 56.1g, the less frequent head-to-head collisions (n = 6) resulted in a maximum of 113.5g. The results of this study improve the understanding of head impact exposure in youth female soccer players and inform head impact exposure reduction in youth soccer.

Repetitive head impacts have long-lasting negative effects on the cognition of athletes. For example, repetitive head impacts accumulated by adult professional soccer players throughout their careers result in long-term negative consequences on cognition. However, these effects on youth soccer players have not been extensively studied and need to be further evaluated. The purposes of this study were to quantify head impact exposure in youth elite soccer and to examine the effects of repetitive head impacts on the cognitive function of youth male soccer players. A prospective cohort study of a single boys U13 soccer team of 18 players (12.9 ± 0.2 years of age) was completed throughout a single soccer season (five months in duration). Head impact frequency data were recorded using impact monitoring mouthguards worn during practices and matches and subsequently video-verified. Cognitive function was assessed using cognitive-motor integration (CMI) tasks conducted before the first season match, every subsequent four weeks, and after the last match. Peak path velocity, absolute error, reaction time, full path movement time, and the number of direction reversals were CMI task outcome measures. Over a single soccer season, 1089 head impacts occurred with more head impacts occurring in practices (62.7%) than matches (37.3%). Midfielders experienced the most head impacts during practices (53.6% of practice impacts), and defenders experienced the most head impacts during matches (47.8% of match impacts). Repetitive head impact exposure by position was associated with significant decreases in absolute error (p < 0.001), increases in peak velocity (p < 0.001), and increases in reaction time (p < 0.001). Repetitive head impacts within a single soccer season were associated with measurable declines in some aspects of youth soccer players' cognitive function. Therefore, coaches should aim to reduce the number of head impacts experienced by male youth soccer players with a specific focus on reducing head impact exposure during practices.