Related Experiment Video
Updated: Jul 30, 2025
A Test Bed to Examine Helmet Fit and Retention and Biomechanical Measures of Head and Neck Injury in Simulated Impact
Published on: September 21, 2017
Quantifying head impact biomechanical differences between commonly employed cleaning levels: a critical research
Rachel K Le1,2, Landon B Lempke3, Melissa N Anderson4
1Department of Exercise Science, Mercer University, Macon, Georgia, USA.
Introduction:
Wearable accelerometry devices quantify on-field frequency and severity of head impacts to further improve sport safety. Commonly employed post-data collection cleaning techniques may affect these outcomes.
Objective:
Our purpose was to compare game impact rates and magnitudes between three different cleaning levels (Level-1: impacts recorded within start and end times, Level-2: impacts during pauses/breaks removed, Level-3: video verified) for male youth tackle football.
Methods:
Participants (n = 23, age = 10.9 ± 0.3 yrs, height = 150.0 ± 8.3 cm, mass = 41.6 ± 8.4 kg) wore Triax SIM-G sensors throughout Fall 2019. Impact rates, ratios (IRRs), and 95% confidence intervals (95%CI) were used to compare levels. Random-effects general linear models were used to compare peak linear acceleration (PLA;g) and angular velocity (PAV;rads/s).
Results:
Level-1 resulted in higher impact rates (4.57; 95%CI = 4.14-5.05) compared to Level-2 (3.09; 95%CI = 2.80-3.42; IRR = 1.48; 95%CI = 1.34-1.63) and Level-3 datasets (2.56; 95%CI = 2.30-2.85; IRR = 1.78; 95%CI = 1.60-1.98). Level-2 had higher impact rates compared to Level-3 (1.21; 95%CI = 1.08-1.35). Level-1 resulted in higher PAV than Level-2 and Level-3 (p < 0.001) datasets. PLA did not differ across datasets (p = 0.296).
Conclusions:
Head impact data should be filtered of pauses/breaks, and does not substantially differ outcome estimates compared to time-intensive video verification.
