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The use of head kinematic measurement devices has recently proliferated owing to technology advances that make such measurement more feasible. In parallel, demand to understand the biomechanics of head impacts and injury in sports and the military has increased as the burden of such loading on the brain has received focused attention. As a result, the field has matured to the point of needing methodological guidelines to improve the rigor and consistency of research and reduce the risk of scientific bias. To this end, a diverse group of scientists undertook a comprehensive effort to define current best practices in head kinematic measurement, culminating in a series of manuscripts outlining consensus methodologies and companion summary statements. Summary statements were discussed, revised, and voted upon at the Consensus Head Acceleration Measurement Practices (CHAMP) Conference in March 2022. This manuscript summarizes the motivation and methods of the consensus process and introduces recommended reporting checklists to be used to increase transparency and rigor of future experimental design and publication of work in this field. The checklists provide an accessible means for researchers to apply the best practices summarized in the companion manuscripts when reporting studies utilizing head kinematic measurement in sport and military settings., (© 2022. The Author(s).)

Consideration of position-specific features of the NFL concussion environment could enable improved risk mitigation through the design of position-specific helmets to improve self-protection as well as protection for the other player with whom the contact occurs. The purpose of this paper is to quantify position-specific features of scenarios resulting in concussions to NFL players, and the players they contact, by reviewing all game footage (broadcast and non-broadcast) over 4 seasons. Position-specific features were documented for 647 concussions in which a primary exposure could be visualized, including impact source, helmet impact location, activity, and the other player with whom the contact occurred. Findings include the over-representation of helmet-to-ground impacts to the rear of the quarterback's helmet, the high frequency of impacts to the side (upper) location of both concussed players and the players they contacted regardless of position, and distinct differences in the circumstances of concussions to cornerbacks and safeties. The study shows that some features of concussion scenarios are common to all positions, but several position-specific features exist and can inform the design of position-specific helmets for NFL players.

Background : The use of video review to document visible signs (VS) of sport-related concussion in the National Football League (NFL) is a novel method to recognize head injuries. Hypothesis/Purpose : The current pilot studies used varying methodologies to (1) examine the frequency of VS in concussed NFL players using the Australian Football League's (AFL) checklist, and (2) assess the reliability of VS between non-expert and expert raters. Study design : Cohort study Methods : In the first pilot study, two non-expert raters rated VS of SRC occurring in the 2015 NFL season ( n =  96) using a single VS from the AFL checklist. Based on this pilot study, two expert raters then rated VS of SRC during the 2017 NFL season ( n =  211) using all VS from the AFL checklist. The frequency, total percent agreement (TPA), and reliability (kappa coefficients) were calculated for all VS of concussion for the two seasons. Kappa agreement was classified as fair (.41-.60), moderate (.61-.80), or substantial (.81-1.00). Significance was set at p <  .05. Results : The most frequent VS of concussion identified by both non-expert and expert raters were no behavior observed, slow to get up, and motor incoordination . The least frequent VS were impact seizure, blank/vacant look, and facial injury. For non-expert raters , the average TPA for VS ranged from 84% to 100% and kappa coefficients ranged from .52 to .68. For expert raters , the average TPA ranged from 83% to 100%, and kappa coefficients ranged from .56 to .86. Conclusion : In these preliminary analyses, use of multiple VS was a superior methodology, and the reliability of VS rating was stronger for experts. Due to the inherent differences in gameplay and protective equipment used in the NFL compared to other professional sports, it is our hope these data can generate new ways to improve existing practices and identify potentially novel VS of SRC.

The relationship between laboratory and on-field performance of football helmets was assessed for 31 football helmet models selected from those worn by players in the 2015-2019 National Football League (NFL) seasons. Linear impactor tests were conducted with helmets placed on an instrumented Hybrid III head and neck assembly mounted on a sliding table. Based on impacts to each helmet at six impact locations and three velocities, a helmet performance score (HPS) was calculated using a linear combination of the head injury criterion (HIC) and the diffuse axonal multi-axis general evaluation (DAMAGE). To determine the on-field performance of helmets, helmet model usage, player participation, and incident concussion data were collected from the five NFL seasons and used to calculate helmet model-specific concussion rates. Comparison of laboratory HPS to the helmet model-specific concussion rates on a per play basis showed a positive correlation (r 2  = 0.61, p < 0.001) between laboratory and on-field performance of helmet models, indicating that helmets which exhibited reduced impact severity in the laboratory tests were also generally associated with lower concussion rates on-field. Further analysis showed that NFL-prohibited helmet models exhibited a significantly higher odds of concussion (OR 1.24; 95% CI 1.04-1.47; p = 0.017) relative to other helmet models.

As more is learned about injury mechanisms of concussion and scenarios under which injuries are sustained in football games, methods used to evaluate protective equipment must adapt. A combination of video review, videogrammetry, and laboratory reconstructions was used to characterize concussive impacts from National Football League games during the 2015-2017 seasons. Test conditions were generated based upon impact locations and speeds from this data set, and a method for scoring overall helmet performance was created. Head kinematics generated using a linear impactor and sliding table fixture were comparable to those from laboratory reconstructions of concussive impacts at similar impact conditions. Impact tests were performed on 36 football helmet models at two laboratories to evaluate the reproducibility of results from the resulting test protocol. Head acceleration response metric, a head impact severity metric, varied 2.9-5.6% for helmet impacts in the same lab, and 3.8-6.0% for tests performed in a separate lab when averaged by location for the models tested. Overall inter-lab helmet performance varied by 1.1 ± 0.9%, while the standard deviation in helmet performance score was 7.0%. The worst helmet performance score was 33% greater than the score of the best-performing helmet evaluated by this study.

Sports concussions offer a unique opportunity to study head kinematics associated with mild traumatic brain injury. In this study, a model-based image matching (MBIM) approach was employed to analyze video footage of 57 concussions which occurred in National Football League (NFL) games. By utilizing at least two camera views, higher frame rate footage (> 60 images s -1 ), and laser scans of the field and helmets involved in each case, it was possible to calculate the change in velocity of the helmet during impact in six degrees of freedom. The average impact velocity for these concussive events was 8.9 ± 2.0 m s -1 . The average changes in translational and rotational velocity for the concussed players' helmets were 6.6 ± 2.1 m s -1 and 29 ± 13 rad s -1 , respectively. The average change in translational velocity was higher for helmet-to-ground (n = 16) impacts compared to helmet-to-helmet (n = 30) or helmet-to-shoulder (n = 11) events (p < 0.001), while helmet-to-shoulder impacts had a smaller change in rotational velocity compared to the other impact sources (p < 0.001). By quantifying the impact velocities and locations associated with concussive impacts in professional American football, this study provides information that may be used to improve upon current helmet testing methodologies.

Background: On-field visible signs (VS) are used to help identify sport-related concussion (SRC) in the National Football League (NFL). However, the predictive utility of a VS checklist for SRC is unknown., Objective: To report the frequency, sensitivity, specificity, and predictive value of VS in a cohort of NFL athletes., Methods: On-field VS ratings from 2 experts who independently reviewed video footage of a cohort of 251 injury plays that resulted in an SRC diagnosis (n = 211) and no diagnosis (n = 40) from the 2017 NFL season were examined. The frequency, sensitivity, specificity, and a receiver operating characteristic (ROC) curve with area under the curve (AUC) were calculated for each VS., Results: Slow to get up (65.9%) and motor incoordination (28.4%) were the most frequent VS in concussed athletes, and slow to get up (60.0%) was the most common VS among nonconcussed athletes. The most sensitive VS was slow to get up (66%); the most specific signs in concussed NFL athletes were blank/vacant look and impact seizure (both 100%). Approximately 26% of concussed NFL players did not exhibit a VS, and the overall sensitivity and specificity for the VS checklist to detect SRC were 73% and 65%, respectively. The VS checklist demonstrated "poor" ability to discriminate between SRC and non-SRC groups (AUC = 0.66)., Conclusion: In the NFL, the diagnosis of concussion cannot be made from on-field VS alone. The VS checklist is one part of the comprehensive sideline/acute evaluation of concussion, and the diagnosis remains a multimodal clinical decision., (Copyright © 2020 by the Congress of Neurological Surgeons.)

Background: Head kinematics generated by laboratory reconstructions of professional football helmet impacts have been applied to computational models to study the biomechanics of concussion. Since the original publication of this data, techniques for evaluating accelerometer consistency and error correction have been developed. This study applies these techniques to the original reconstruction data and reanalyzes the results given the current state of concussion biomechanics., Methods: Consistency checks were applied to the sensor data collected in the head of each test dummy. Inconsistent data were corrected using analytical techniques, and head kinematics were recalculated from the corrected data. Reconstruction videos were reviewed to identify artefactual impacts during the reconstruction to establish the region of applicability for simulations. Corrected head kinematics were input into finite element brain models to investigate strain response to the corrected dataset., Findings: Multiple reconstruction cases had inconsistent sensor arrays caused by a problematic sensor; corrections to the arrays caused changes in calculated rotational head motion. These corrections increased median peak angular velocity for the concussion cases from 35.6 to 41.5 rad/s. Using the original kinematics resulted in an average error of 20% in maximum principal strain results for each case. Simulations of the reconstructions also demonstrated that simulation lengths less than 40 ms did not capture the entire brain strain response and under-predicted strain., Interpretation: This study corrects data that were used to determine concussion risk, and indicates altered head angular motion and brain strain response for many reconstructions. Conclusions based on the original data should be re-examined based on this new study., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Concussions in American football remain a high priority of sports injury prevention programs. Detailed video review provides important information on causation, the outcomes of rule changes, and guidance on future injury prevention strategies., Purpose: Documentation of concussions sustained in National Football League games played during the 2015-2016 and 2016-2017 seasons, including consideration of video views unavailable to the public., Study Design: Descriptive epidemiology study., Methods: All reported concussions were reviewed with all available video footage. Standardized terminology and associated definitions were developed to describe and categorize the details of each concussion., Results: Cornerbacks sustained the most concussions, followed by wide receivers, then linebackers and offensive linemen. Half (50%) of concussions occurred during a passing play, 28% during a rushing play, and 21% on a punt or kickoff. Tackling was found to be the most common activity of concussed players, with the side of the helmet the most common helmet impact location. The distribution of helmet impact source-the object that contacted the concussed player's helmet-differed from studies of earlier seasons, with a higher proportion of helmet-to-body impacts (particularly shoulder) and helmet-to-ground impacts and with a lower proportion of helmet-to-helmet impacts. Helmet-to-ground concussive impacts were notable for the high prevalence of impacts to the back of the helmet and their frequency during passing plays., Conclusion: Concussion causation scenarios in the National Football League have changed over time., Clinical Relevance: The results of this study suggest the need for expanded evaluation of concussion countermeasures beyond solely helmet-to-helmet test systems, including consideration of impacts with the ground and with the body of the opposing player. It also suggests the possibility of position-specific countermeasures as part of an ongoing effort to improve safety.