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Biomechanics

Biomechanics - Poster Session D

Poster D8 - Methodology for Identifying Sequential Acceleration Events and their Prevalence in Youth Football Using an Instrumented Mouthpiece

Friday, October 25, 2024
3:30 PM - 4:30 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Football is one of the most popular youth sports in the United States, despite having one of the highest rates of concussions [1]. There is rising concern for repetitive non-concussive head acceleration events (HAEs) that may pose short and long-term risks to brain health [3, 4, 5]. Previous studies have examined characteristics of HAEs using instrumented mouthguards and only reporting the peaks of linear acceleration, resultant acceleration, and rotational velocity over a single impact recording [2]. In some instances, two HAEs occur close in time following the initial trigger (i.e. an event exceeding the pre-determined trigger threshold), where the second event meets the specification of a trigger but occurs close enough in time that it is included in the recording window of the first event. The objective of this study is to develop a methodology to detect sequential HAEs within a single impact recording and characterize the prevalence of these events in a sample of American youth football HAE events.

Materials and

Methods:  A total of 32 youth football athletes (ages 11-14) were enrolled in this study from two teams within the same governing body over the course of a single season. Written assent was obtained from participants and consent was obtained from each participants’ guardians. Data was recorded using a custom-fit acrylic mouthpiece sensor containing a triaxial accelerometer and gyroscope [7]. These sensors were configured to collect data upon meeting the trigger criterion: linear acceleration exceeding 5g on any axis for a minimum of 3 ms (19 consecutive samples). Each recording included 15 milliseconds of data pre-trigger and 45 milliseconds post-trigger, sampled at 6400 Hz. Analysis of the recorded kinematic signals was performed using custom MATLAB code designed to identify Head Acceleration Events (HAEs). All samples meeting the trigger criterion were identified. Continuous trigger regions (i.e., data maintained above 5g with 1 sample of separation) were merged together, and a separation distance, defined as the number of samples between distinct trigger regions, was calculated. The 95th percentile separation distance across all trigger regions was computed and used to calculate a minimum separation distance. Furthermore, a prominence threshold was established to differentiate impactful events from noise or less significant occurrences. This threshold was determined by normalizing the signals and analyzing the prominence of each peak via histograms and boxplots to assess frequency of prominences and variability in separation between identified events.

Results, Conclusions, and Discussions: The triggers of interest showed a range of minimum separation values from 2 samples (0.313 ms) to 237 samples (37 ms), with the 95th percentile separation distance at 66 samples, or 10.3 ms. The signal was normalized and prominence values varied from 0.5 to 0.7, with a threshold set at 0.6 to ensure accurate detection of significant events. Out of 2138 Head Acceleration Events (HAEs) analyzed for sequential occurrences, 41 (2%) were identified as having sequential HAEs. The analysis of duration between sequential HAEs and the magnitude difference between their maximum peaks revealed that the mean, median, and 95th percentile values for the duration between events were 48.5 samples, 30 samples, and 145 samples, respectively. For the magnitude difference between maximum peaks, the mean, median, and 95th percentile values were 1.98 g’s, 1.98 g’s, and 7.29 g’s, respectively. This study successfully developed a methodology for detecting sequential Head Acceleration Events (HAEs) within single impact recordings and assessed their prevalence in youth football. By analyzing data from custom-fit mouthpiece sensors, we identified and characterized cases where multiple HAEs occurred in close succession. The findings reveal that 2% of the recorded HAEs involved sequential impacts, suggesting that such events are not only detectable but also potentially significant. The analysis of time and magnitude differences between sequential HAEs showed a mean duration of 11.14 samples between events and a mean magnitude difference of 1.98 g’s, providing valuable insights into these impacts. This advancement in detection and characterization contributes to a biomechanical understanding of head impacts in youth football. The methodology developed herein could improve the reporting of HAEs occurring over a season, thereby aiding in the development of targeted interventions. By highlighting the potential cumulative effects of repeated head trauma, this research underscores the need for continued focus on player safety. The improved detection and analysis of sequential HAEs pave the way for more informed interventions, ultimately enhancing efforts to protect player health and safety.

Acknowledgements (Optional):  The authors would like to thank the football organizations for participating in this study. The authors also thank the National Institutes of Health (NICHD 5K25HD101686-04) and National Science Foundation (Award #1950281) for funding this study.