Helmet Lab

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The Virginia Tech Helmet Lab allows researchers to provide unbiased helmet ratings that allow consumers to make informed decisions when purchasing helmets. The helmet ratings are the culmination of over 10 years of research on head impacts in sports and identify which helmets best reduce concussion risk. Please contact the Helmet Lab with any questions about this research.

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Recent Submissions

Now showing 1 - 15 of 15
  • Equestrian STAR: Development of an Experimental Methodology for Assessing the Biomechanical Performance of Equestrian Helmets
    Duma, Lauren A.; Begonia, Mark T.; Miller, Barry; Jung, Caitlyn; Wood, Matthew; Duma, Brock G.; Rowson, Steven (Springer, 2025-04-28)
    Purpose: The current equestrian helmet standards set minimal requirements for passing helmets, highlighting the need for a rating system that differentiates helmets based on their impact performance. This study’s objectives were to compare equestrian helmet impact response kinematics between linear-driven and oblique impact conditions and then to evaluate the effect of incorporating oblique drop tests into a previously established equestrian helmet rating system, Equestrian STAR. Methods: Oblique drop tests were conducted with 45 equestrian helmet models at two impact locations, front boss and rear boss, at an impact velocity of 6.56 m/s. The resulting peak linear and rotational head accelerations were compared to those measured during linear-driven pendulum impacts on the same helmet models. A total of 720 impact tests were performed, making this the largest published study on equestrian helmets to date. Equestrian STAR was modified to include both pendulum and oblique impacts by computing and summing weighted concussion risks for each test condition. Results: Oblique impacts had peak linear accelerations ranging from 105.8 to 204.5 g and peak rotational accelerations ranging from 3304 to 13854 rad/s2. Between the linear-driven and oblique impacts, peak linear acceleration was weakly correlated (R2 = 0.34, p < 0.001), while peak rotational acceleration was not correlated (R2 = 0.04, p = 0.21). Equestrian STAR scores calculated using both pendulum and oblique impacts suggested that the worst-performing helmet on both systems had nearly four times the concussion risk as the best-performing. Conclusion: Pendulum and oblique impacts have different methods of generating head rotation, which can highlight different modes of helmet performance. The updated Equestrian STAR helmet rating system differentiates between high-performing and low-performing helmets, enabling equestrians to purchase helmets best at reducing concussion risk and providing companies with a process to compare their helmet designs.
  • Equestrian STAR Protocol
    Duma, Lauren A.; Begonia, Mark T.; Miller, Barry; Rowson, Steven (Virginia Tech, 2025-05-19)
    This document details the protocol used to rate equestrian helmets based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Polo Helmet Rotational Testing
    Rowson, Steven; Begonia, Mark T. (Virginia Tech, 2023-05-22)
    Present polo helmet testing methods only assess linear acceleration, neglecting the evaluation of a helmet's ability to reduce rotational acceleration. Both linear and rotational accelerations are key predictors of brain injuries. Therefore, understanding these measures is crucial for gauging the risk associated with each helmet. This report describes the results of a test series requested by the United States Polo Association Safety Committee that evaluated current polo helmets under rotational loading conditions.
  • Equestrian Standards Helmet Impact Criteria
    Helmet Lab (2022-12-06)
    A comparison sheet of standards for testing equestrian helmets.
  • Whitewater STAR Methodology
    Duma, Brock; Begonia, Mark T.; Miller, Barry; Rowson, Steven; Duma, Stefan (2022-09-08)
    This document details the protocol used to rate whitewater helmets based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Snow Sport Helmet STAR Protocol
    Keim, Summer; Begonia, Mark T.; Kieffer, Emily E.; Rowson, Steven (Virginia Tech, 2022-02-11)
    This document details the protocol used by the Virginia Tech Helmet Ratings to rate snow sport helmets based on concussion risk.
  • Hockey STAR Methodology
    Begonia, Mark T.; Tyson, Abigail M.; Rowson, Bethany M.; Rowson, Steven (Virginia Tech, 2022-02-08)
    This document details the protocol used by the Virginia Tech Helmet Ratings to rate hockey helmets based on concussion risk.
  • Implementing Head Impact Sensors in Collegiate Men’s and Women’s Rugby: Successes and Challenges in Characterizing Concussion
    Kieffer, Emily E.; Rowson, Steven (Virginia Tech, 2022-01-29)
    Head impact sensors allow researchers to learn more about human tolerance to head impact exposure and concussion. Previous on-field data collection has worked to quantify concussion biomechanics, based primarily on helmeted male athletes. Data from unhelmeted and female athletes still need to be collected and quantified to understand how concussion tolerance varies by sex and loading environment. The primary goal of this study was to instrument collegiate rugby players with head impact sensors embedded in mouthguards and to report head impact and concussion biomechanics. Over four seasons of data collection, four males and 15 females sustained concussions. To reduce underreporting, we collected weekly graded symptom surveys from all players. Kinematics were only collected for two male concussions and three female concussions due to different challenges with the instrumentation. The secondary goal of this study was to discuss head impact sensors that are used on-field and explore their practicality and limitations. We present our experience using two instrumented mouthguards, the Wake Forest Instrumented Retainer and the Prevent Biometrics Intelligent Instrumented Mouthguard, to measure head impacts in athletes. Not enough injury data were collected to quantify unhelmeted concussion tolerance. Still, the following reports may provide foundational and reference cases for future research, in addition to discussion of data quality, sex-specific athlete compliance, general usability, and provide recommendations for future head impact sensor use.
  • Virginia Tech Hockey Helmet Ratings Memorandum
    Rowson, Steven; Begonia, Mark T.; Rowson, Bethany M.; Duma, Stefan M. (Virginia Tech, 2022-01-25)
    This memorandum serves to reiterate the goals of the Virginia Tech Helmet Ratings, discuss the hockey helmet ratings, and announce an update to the exposure weightings and star thresholds used to rate hockey helmets.
  • STAR Methodology for Rugby Headgear
    Kieffer, Emily E.; Rowson, Steven (Virginia Tech, 2021-07-13)
    This document details the protocol used to rate rugby headgear based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Varsity Football STAR Methodology
    Tyson, Abigail M.; Rowson, Steven (Virginia Tech, 2020-12)
    This document details the protocol used to rate adult football helmets based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Flag Football Headgear STAR Protocol
    Begonia, Mark T.; Rowson, Steven (Virginia Tech, 2019-06-30)
    This document details the protocol used to rate flag football headgear based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Youth Football Helmet STAR Methodology
    Campolettano, Eamon T.; Sproule, David W.; Begonia, Mark T.; Rowson, Steven (Virginia Tech, 2019-03-19)
    This document details the protocol used by the Virginia Tech Helmet Ratings to rate youth football helmets based on concussion risk.
  • Bicycle Helmet STAR Protocol
    Bland, Megan L.; McNally, Craig; Rowson, Steven (Virginia Tech, 2018-06-25)
    This document details the protocol used to rate adult bicycle helmets based on concussion risk according to the Virginia Tech Helmet Ratings.
  • Soccer Headgear STAR Protocol
    Tyson, Abigail M.; Press, Jaclyn; Rowson, Steven (Virginia Tech, 2018-03-30)
    This document details the protocol used to rate soccer headgear based on concussion risk according to the Virginia Tech Helmet Ratings.