Characterization of Concussive Events in Professional American Football Using Videogrammetry

Physiological and Biomechanical Monitoring in American Football Players: A Scoping Review

American football is the sport with the highest rates of concussion injuries. Biomedical engineering applications may support athletes in monitoring their injuries, evaluating the effectiveness of their equipment, and leading industrial research in this sport. This literature review aims to report on the applications of biomedical engineering research in American football, highlighting the main trends and gaps. The review followed the PRISMA guidelines and gathered a total of 1629 records from PubMed (n = 368), Web of Science (n = 665), and Scopus (n = 596). The records were analyzed, tabulated, and clustered in topics. In total, 112 studies were selected and divided by topic in the biomechanics of concussion (n = 55), biomechanics of footwear (n = 6), biomechanics of sport-related movements (n = 6), the aerodynamics of football and catch (n = 3), injury prediction (n = 8), heat monitoring of physiological parameters (n = 8), and monitoring of the training load (n = 25). The safety of players has fueled most of the research that has led to innovations in helmet and footwear design, as well as improvements in the understanding and prevention of injuries and heat monitoring. The other important motivator for research is the improvement of performance, which has led to the monitoring of training loads and catches, and studies on the aerodynamics of football. The main gaps found in the literature were regarding the monitoring of internal loads and the innovation of shoulder pads.

Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis

Head impact measurement devices enable opportunities to collect impact data directly from humans to study topics like concussion biomechanics, head impact exposure and its effects, and concussion risk reduction techniques in sports when paired with other relevant data. With recent advances in head impact measurement devices and cost-effective price points, more and more investigators are using them to study brain health questions. However, as the field's literature grows, the variance in study quality is apparent. This brief paper aims to provide a high-level set of key considerations for the design and analysis of head impact measurement studies that can help avoid flaws introduced by sampling biases, false data, missing data, and confounding factors. We discuss key points through four overarching themes: study design, operational management, data quality, and data analysis.

Consensus Head Acceleration Measurement Practices (CHAMP): Origins, Methods, Transparency and Disclosure

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.

Concussion biomechanics, head acceleration exposure and brain injury criteria in sport: a review

There are mounting concerns surrounding the risk of neurodegenerative diseases and complications associated with concussion incidence and repetitive head acceleration events (HAE) in sport. The aim of this review is to provide an overview of concussion biomechanics, head acceleration exposure and brain injury criteria in sport. Rotational head motion appears to be the primary contributor to brain injury risk due to the unique mechanical properties of the brain and its location within the body. There is a growing evidence base of different biomechanical brain injury mechanisms, including those involving repetitive HAE. Historically, many studies on concussion biomechanics, head acceleration exposure and brain injury criteria in sport have been limited by validity of the biomechanical approaches undertaken. Biomechanical approaches such as instrumented mouthguards and subject-specific finite element (FE) brain models provide a unique opportunity to develop greater brain injury criteria and aid in on-field athlete removal. Implementing these approaches on a large-scale can gain insight into potential risk factors within sports and certain athletes/cohorts who sustain a greater number and/or severity of HAE throughout their playing career. These findings could play a key role in the development of concussion prevention strategies and techniques that mitigate the severity of HAE in sport.

Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players

Background: Exposure to thousands of head and body impacts during a career in contact and collision sports may contribute to current or later life issues related to brain health. Wearable technology enables the measurement of impact exposure. The validation of impact detection is required for accurate exposure monitoring. In this study, we present a method of automatic identification (classification) of head and body impacts using an instrumented mouthguard, video-verified impacts, and machine-learning algorithms.

Methods: Time series data were collected via the Nexus A9 mouthguard from 60 elite level men (mean age = 26.33; SD = 3.79) and four women (mean age = 25.50; SD = 5.91) from the Australian Rules Football players from eight clubs, participating in 119 games during the 2020 season. Ground truth data labeling on the captures used in this machine learning study was performed through the analysis of game footage by two expert video reviewers using SportCode and Catapult Vision. The visual labeling process occurred independently of the mouthguard time series data. True positive captures (captures where the reviewer directly observed contact between the mouthguard wearer and another player, the ball, or the ground) were defined as hits. Spectral and convolutional kernel based features were extracted from time series data. Performances of untuned classification algorithms from scikit-learn in addition to XGBoost were assessed to select the best performing baseline method for tuning.

Results: Based on performance, XGBoost was selected as the classifier algorithm for tuning. A total of 13,712 video verified captures were collected and used to train and validate the classifier. True positive detection ranged from 94.67% in the Test set to 100% in the hold out set. True negatives ranged from 95.65 to 96.83% in the test and rest sets, respectively.

Discussion and conclusion: This study suggests the potential for high performing impact classification models to be used for Australian Rules Football and highlights the importance of frequencies <150 Hz for the identification of these impacts.

Development of a Low-Power Instrumented Mouthpiece for Directly Measuring Head Acceleration in American Football

Instrumented mouthpieces (IM) offer a means of measuring head impacts that occur in sport. Direct measurement of angular head kinematics is preferential for accuracy; however, existing IMs measure angular velocity and differentiate the measurement to calculate angular acceleration, which can limit bandwidth and consume more power. This study presents the development and validation of an IM that uses new, low-power accelerometers for direct measurement of linear and angular acceleration over a broad range of head impact conditions in American football. IM sensor accuracy for measuring six-degree-of-freedom head kinematics was assessed using two helmeted headforms instrumented with a custom-fit IM and reference sensor instrumentation. Head impacts were performed at 10 locations and 6 speeds representative of the on-field conditions associated with injurious and non-injurious impacts in American football. Sensor measurements from the IM were highly correlated with those from the reference instrumentation located at the maxilla and skull center of gravity. Based on pooled data across headform and impact location, R² ≥ 0.94, mean absolute error (AE) ≤ 7%, and mean relative impact angle ≤ 11° for peak linear and angular acceleration and angular velocity while R² ≥ 0.90 and mean AE ≤ 7% for kinematic-based injury metrics used in helmet tests.

Three-dimensional video analysis of helmet-to-ground impacts in North American youth football

This study presents a video analysis of helmet-to-ground impacts in youth football (≤14 years). A total of 21 non-injurious helmet-to-ground impact cases were assessed from game video of two age divisions (9-12 years: n = 9; 13-14 years: n = 12) using a novel multi-camera videogrammetry approach. Descriptive parameters related to the game situation and impact mechanisms were documented. Motion analysis software was used to manually track and compute three-dimensional helmet kinematics and uncertainty of the motion tracking analysis was assessed. Overall, the impact cases primarily followed a body-to-body, body-to-ground, helmet-to-ground contact progression. Impact locations on the helmet were mostly distributed across the rear and side helmet shell. The resultant pre-impact velocities for these cases averaged 4.04 ± 1.24 m/s at an angle of -49.6° to the ground. The average resultant impact-induced change in helmet velocity was 3.32 ± 1.14 m/s; the time interval associated with the duration of helmet-to-ground contact was approximately 0.06 s. The average maximum uncertainty (±) error of the position coordinates from the helmet tracking was 1.5 ± 0.3 cm. In summary, this video-based methodology can effectively be used to quantify helmet impact velocities and locations in youth football games. To date, the acquisition of such information has largely been limited to professional football game footage. Therefore, the data reported here may help inform the development of more representative assessment methods for youth-specific helmet test standards.

The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players

This study sought to evaluate head accelerations in both players involved in a football collision. Players on two opposing Canadian university teams were equipped with helmet mounted sensors during one game per season, for two consecutive seasons. A total of 276 collisions between 58 instrumented players were identified via video and cross-referenced with sensor timestamps. Player involvement (striking and struck), impact type (block or tackle), head impact location (front, back, left and right), and play type were recorded from video footage. While struck players did not experience significantly different linear or rotational accelerations between any play types, striking players had the highest linear and rotational head accelerations during kickoff plays (p ≤ .03). Striking players also experienced greater linear and rotational head accelerations than struck players during kickoff plays (p = .001). However, struck players experienced greater linear and rotational accelerations than striking players during kick return plays (p ≤ .008). Other studies have established that the more severe the head impact, the greater risk for injury to the brain. This paper's results highlight that kickoff play rule changes, as implemented in American college football, would decrease head impact exposure of Canadian university football athletes and make the game safer.