Position-based assessment of head impact frequency, severity, type, and location in high school American football

Introduction

Research on head impact characteristics, especially position-specific investigations in football, has predominantly focused on collegiate and professional levels, leaving a gap in understanding the risks faced by high school players. Therefore, this study aimed to investigate the effect of three factors-player position, impact location, and impact type-on the frequency, severity, and characteristics of impacts in high school American football. Additionally, we examined whether and how player position influences the distribution of impact locations and types.

Methods

Sixteen high school football players aged 14 to 17 participated in this study. Validated mouthguard sensors measured head impact kinematics, including linear acceleration, angular acceleration, and angular velocity across ten games, and were used to identify impact locations on the head. Video recordings verified true impacts, player position, and impact type at the moment of each recorded impact. Head impact kinematics were input into a head finite element model to determine the 95th percentile of the maximum principal strain and strain rate. Several novel and systematic approaches, such as normalization, binning, and clustering, were introduced and utilized to investigate the frequency and severity of head impacts across the three aforementioned factors while addressing some of the limitations of previous methodologies in the field. To that end, the number of recorded impacts for each player position during each game was divided by the number of players in that position, and then averaged across ten games. Instead of averaging, impacts were categorized into four severity bins: low, mid-low, mid-high and high. Clusters for the three factors were also identified according to the characteristics of impacts.

Results and Discussion

Results revealed that offensive linemen and running backs experienced a higher normalized frequency and more severe impacts across all head kinematics and brain tissue deformation parameters. Frontal impacts, resulting from "head-to-head" impacts, were the most frequent and severe impact locations. The distributions of impact location and type for each specific position were distinct. Offensive linemen had the highest proportion of frontal impacts, while quarterbacks and centerbacks had more impacts at the rear location. These findings can inform interventions in game regulations, training practices, and helmet design to mitigate injury risks in high school football.

Identifying Factors Associated with Head Impact Kinematics and Brain Strain in High School American Football via Instrumented Mouthguards

Repeated head impact exposure and concussions are common in American football. Identifying the factors associated with high magnitude impacts aids in informing sport policy changes, improvements to protective equipment, and better understanding of the brain's response to mechanical loading. Recently, the Stanford Instrumented Mouthguard (MiG2.0) has seen several improvements in its accuracy in measuring head kinematics and its ability to correctly differentiate between true head impact events and false positives. Using this device, the present study sought to identify factors (e.g., player position, helmet model, direction of head acceleration, etc.) that are associated with head impact kinematics and brain strain in high school American football athletes. 116 athletes were monitored over a total of 888 athlete exposures. 602 total impacts were captured and verified by the MiG2.0's validated impact detection algorithm. Peak values of linear acceleration, angular velocity, and angular acceleration were obtained from the mouthguard kinematics. The kinematics were also entered into a previously developed finite element model of the human brain to compute the 95th percentile maximum principal strain. Overall, impacts were (mean ± SD) 34.0 ± 24.3 g for peak linear acceleration, 22.2 ± 15.4 rad/s for peak angular velocity, 2979.4 ± 3030.4 rad/s² for peak angular acceleration, and 0.262 ± 0.241 for 95th percentile maximum principal strain. Statistical analyses revealed that impacts resulting in Forward head accelerations had higher magnitudes of peak kinematics and brain strain than Lateral or Rearward impacts and that athletes in skill positions sustained impacts of greater magnitude than athletes in line positions. 95th percentile maximum principal strain was significantly lower in the observed cohort of high school football athletes than previous reports of collegiate football athletes. No differences in impact magnitude were observed in athletes with or without previous concussion history, in athletes wearing different helmet models, or in junior varsity or varsity athletes. This study presents novel information on head acceleration events and their resulting brain strain in high school American football from our advanced, validated method of measuring head kinematics via instrumented mouthguard technology.

Head Rotational Kinematics, Tissue Deformations, and Their Relationships to the Acute Traumatic Axonal Injury

Head rotational kinematics and tissue deformation metrics obtained from finite element models (FEM) have the potential to be used as traumatic axonal injury (TAI) assessment criteria and headgear evaluation standards. These metrics have been used to predict the likelihood of TAI occurrence; however, their ability in the assessment of the extent of TAI has not been explored. In this study, a pig model of TAI was used to examine a wide range of head loading conditions in two directions. The extent of TAI was quantified through histopathology and correlated to the FEM-derived tissue deformations and the head rotational kinematics. Peak angular acceleration and maximum strain rate of axonal fiber and brain tissue showed relatively good correlation to the volume of axonal injury, with similar correlation trends for both directions separately or combined. These rotational kinematics and tissue deformations can estimate the extent of acute TAI. The relationships between the head kinematics and the tissue strain, strain rate, and strain times strain rate were determined over the experimental range examined herein, and beyond that through parametric simulations. These relationships demonstrate that peak angular velocity and acceleration affect the underlying tissue deformations and the knowledge of both help to predict TAI risk. These relationships were combined with the injury thresholds, extracted from the TAI risk curves, and the kinematic-based risk curves representing overall axonal and brain tissue strain and strain rate were determined for predicting TAI. After scaling to humans, these curves can be used for real-time TAI assessment.