A Vibration-Based Concussion Mechanism - Steven Rowson (Annals of Biomedical Engineering, 2026)
Concussion biomechanics are understood through rigid-body head kinematics during long-duration impacts. However, short-duration head impacts represent a distinct loading regime in which skull vibration and flexural deformation may play a role in injury mechanisms not captured by traditional metrics. Here, I suggest that transient excitation of skull flexural modes could help explain how impacts with low-magnitude rigid-body accelerations produce concussion-like signs and symptoms. This mechanism remains a hypothesis and is intended to complement, not replace, established strain-based mechanisms.

Development of a Fall-Specific Impact Testing Method to Evaluate Safety Helmet Performance and Injury Risk - Susanna M. Gagliardi; Nicole E.-P. Stark; Mark T. Begonia; Michael L. Madigan; Steven Rowson (Annals of Biomedical Engineering, 2026)
Purpose Despite falls accounting for the greatest number of fatal and non-fatal work-related traumatic brain injuries, current standards do not evaluate safety helmets under impact conditions representative of fall scenarios. This study’s objective was to develop a test method that evaluates safety helmets under impact scenarios representative of falls. A Construction STAR rating system that quantitatively compares safety helmet performance in the context of concussion and skull fracture risk is also outlined. Methods A multi-step approach that combined information from previous literature, Occupational Safety and Health Administration (OSHA) accident reports, and oblique impact tests were used to develop a fall-specific safety helmet test methodology. The test methodology consisting of three impact locations (front boss, rear boss, and rear), two impact velocities (5.5 and 6.8 m/s), and a 25-degree anvil was executed on a representative subset of one Type I and four Type II models. STAR scores, combining concussion and skull fracture risk, were calculated for each model and compared. Results STAR scores demonstrated that Type II helmets reduced concussion risk by 32.7% and skull fracture risk by 57.5% when compared to the Type I model. Large variations in Type II performance were observed, with the top-performing Type II helmets reducing concussion risk by 28.7 and 33.2% compared to bottom-performing models. Conclusions Type II helmets offer substantial benefits in head protection compared to Type I models for oblique fall-related impacts. By including both skull fracture and concussion risk in the STAR score, the proposed methodology can differentiate high and low-performing safety helmets.

How Shell Add-On Products Influence Varsity Football Helmet Performance? - Nicole E.-P. Stark; Mark T. Begonia; Caitlyn Jung; Steven Rowson (Annals of Biomedical Engineering, 2024)
Purpose The study purpose was to investigate the laboratory-based performance of three commercially available shell add-on products under varsity-level impact conditions. Methods Pendulum impact tests were conducted at multiple locations (front, front boss, rear, side) and speeds (3.1, 4.9, 6.4 m/s) using two helmet models. Tests were performed with a single add-on configuration for baseline comparisons and a double add-on configuration to simulate collisions with both players wearing shell add-ons. A linear mixed-effect model was used to evaluate peak linear acceleration (PLA), peak rotational acceleration (PRA), and concussion risk, which was calculated from a bivariate injury risk function, based on shell add-on and test configuration. Results All shell add-ons decreased peak head kinematics and injury risk compared to controls, with the Guardian NXT producing the largest reductions (PLA: 7.9%, PRA: 14.1%, Risk: 34.1%) compared to the SAFR Helmet Cover (PLA: 4.5%, PRA: 9.3%, Risk: 24.7%) and Guardian XT (PLA: 3.2%, PRA: 5.0%, Risk: 15.5%). The same trend was observed in the double add-on test configuration. However, the Guardian NXT (PLA: 17.1%; PRA: 11.5%; Risk: 62.8%) and SAFR Helmet Cover (PLA: 12.2%; PRA: 9.1%; Risk: 52.2%) produced larger reductions in peak head kinematics and injury risk than the Guardian XT (PLA: 5.7%, PRA: 2.2%, Risk: 21.8%). Conclusion In laboratory-based assessments that simulated varsity-level impact conditions, the Guardian NXT was associated with larger reductions in PLA, PRA, and injury risk compared to the SAFR Helmet Cover and Guardian XT. Although shell add-ons can enhance head protection, helmet model selection should be prioritized.

The Influence of Headform Friction and Inertial Properties on Oblique Impact Helmet Testing - Nicole E.-P. Stark; Mark Begonia; Luca Viano; Steven Rowson (Annals of Biomedical Engineering, 2024)
Helmet-testing headforms replicate the human head impact response, allowing the assessment of helmet protection and injury risk. However, the industry uses three different headforms with varying inertial and friction properties making study comparisons difficult because these headforms have different inertial and friction properties that may affect their impact response. This study aimed to quantify the influence of headform coefficient of friction (COF) and inertial properties on oblique impact response. The static COF of each headform condition (EN960, Hybrid III, NOCSAE, Hybrid III with a skull cap, NOCSAE with a skull cap) was measured against the helmet lining material used in a KASK prototype helmet. Each headform condition was tested with the same helmet model at two speeds (4.8 & 7.3 m/s) and two primary orientations (y-axis and x-axis rotation) with 5 repetitions, totaling 100 tests. The influence of impact location, inertial properties, and friction on linear and rotational impact kinematics was investigated using a MANOVA, and type II sums of squares were used to determine how much variance in dependent variables friction and inertia accounted for. Our results show significant differences in impact response between headforms, with rotational head kinematics being more sensitive to differences in inertial rather than frictional properties. However, at high-speed impacts, linear head kinematics are more affected by changes in frictional properties rather than inertial properties. Helmet testing protocols should consider differences between headforms’ inertial and frictional properties during interpretation. These results provide a framework for cross-comparative analysis between studies that use different headforms and headform modifiers.

Sport-Specific Recovery Trajectories for NCAA Collegiate Athletes Following Concussion - Spencer W. Liebel; Kathryn L. Van Pelt; Paul F. Pasquina; Thomas W. McAllister; Michael A. McCrea; Steven P. Broglio; Scott Anderson; Holly Benjamin; Thomas Buckley; Kenneth Cameron; Sara Chrisman; James Clugston; et al. (Annals of Biomedical Engineering, 2024)

Correction: Rotational Head Kinematics in Football Impacts: An Injury Risk Function for Concussion - Steven Rowson; Stefan M. Duma; Jonathan G. Beckwith; Jeffrey J. Chu; Richard M. Greenwald; Joseph J. Crisco; P. Gunnar Brolinson; Ann-Christine Duhaime; Thomas W. Mcallister; Arthur C. Maerlender (Annals of Biomedical Engineering, 2023)

Time Delta Head Impact Frequency: An Analysis on Head Impact Exposure in the Lead Up to a Concussion: Findings from the NCAA-DOD Care Consortium - Jack Seifert; Alok S. Shah; Jaroslaw Harezlak; Steven Rowson; Jason P. Mihalik; Larry Riggen; Stefan Duma; Alison Brooks; Kenneth L. Cameron; Christopher C. Giza; Joshua Goldman; Kevin M. Guskiewicz; et al. (Annals of Biomedical Engineering, 2022)
Sport-related concussions can result from a single high magnitude impact that generates concussive symptoms, repeated subconcussive head impacts aggregating to generate concussive symptoms, or a combined effect from the two mechanisms. The array of symptoms produced by these mechanisms may be clinically interpreted as a sport-related concussion. It was hypothesized that head impact exposure resulting in concussion is influenced by severity, total number, and frequency of subconcussive head impacts. The influence of total number and magnitude of impacts was previously explored, but frequency was investigated to a lesser degree. In this analysis, head impact frequency was investigated over a new metric called ‘time delta’, the time difference from the first recorded head impact of the day until the concussive impact. Four exposure metrics were analyzed over the time delta to determine whether frequency of head impact exposure was greater for athletes on their concussion date relative to other dates of contact participation. Those metrics included head impact frequency, head impact accrual rate, risk weighted exposure (RWE), and RWE accrual rate. Athletes experienced an elevated median number of impacts, RWE, and RWE accrual rate over the time delta on their concussion date compared to non-injury sessions. This finding suggests elevated frequency of head impact exposure on the concussion date compared to other dates that may precipitate the onset of concussion.

American Football Helmet Effectiveness Against a Strain-Based Concussion Mechanism - Kianoosh Ghazi; Mark Begonia; Steven Rowson; Songbai Ji (Annals of Biomedical Engineering, 2022)

Head Impact Exposure in Youth and Collegiate American Football - Grace B. Choi; Eric P. Smith; Stefan M. Duma; Steven Rowson; Eamon Campolettano; Mireille E. Kelley; Derek A. Jones; Joel D. Stitzel; Jillian E. Urban; Amaris Genemaras; Jonathan G. Beckwith; Richard M. Greenwald; et al. (Annals of Biomedical Engineering, 2022)

Laboratory Reconstructions of Real-world Bicycle Helmet Impacts - Ann R. Harlos; Steven Rowson (Annals of Biomedical Engineering, 2021)

Laboratory Reconstructions of Bicycle Helmet Damage: Investigation of Cyclist Head Impacts Using Oblique Impacts and Computed Tomography - Megan L. Bland; Craig McNally; Jessica B. Cicchino; David S. Zuby; Becky C. Mueller; Melissa L. McCarthy; Craig D. Newgard; Paige E. Kulie; Brittany N. Arnold; Steven Rowson (Annals of Biomedical Engineering, 2020)

Do Head Injury Biomechanics Predict Concussion Clinical Recovery in College American Football Players? - Jason P. Mihalik; Avinash Chandran; Jacob R. Powell; Patricia R. Roby; Kevin M. Guskiewicz; Brian D. Stemper; Alok S. Shah; Steven Rowson; Stefan Duma; Jaroslaw Harezlak; Larry Riggen; Steven P. Broglio; et al. (Annals of Biomedical Engineering, 2020)

Concussion Risk Between Individual Football Players: Survival Analysis of Recurrent Events and Non-events - Steven Rowson; Eamon T. Campolettano; Stefan M. Duma; Brian Stemper; Alok Shah; Jaroslaw Harezlak; Larry Riggen; Jason P. Mihalik; Alison Brooks; Kenneth L. Cameron; Steven J. Svoboda; Megan N. Houston; et al. (Annals of Biomedical Engineering, 2020)

High Energy Side and Rear American Football Head Impacts Cause Obvious Performance Decrement on Video - Adam J. Bartsch; Daniel Hedin; Jay Alberts; Edward C. Benzel; Jason Cruickshank; Robert S. Gray; Kenneth Cameron; Megan N. Houston; Tyler Rooks; Gerald McGinty; Erick Kozlowski; Steven Rowson; et al. (Annals of Biomedical Engineering, 2020)

Quantifying Youth Football Helmet Performance: Assessing Linear and Rotational Head Acceleration - Eamon T. Campolettano; Ryan A. Gellner; David W. Sproule; Mark T. Begonia; Steven Rowson (Annals of Biomedical Engineering, 2020)

Development of a Concussion Risk Function for a Youth Population Using Head Linear and Rotational Acceleration - Eamon T. Campolettano; Ryan A. Gellner; Eric P. Smith; Srinidhi Bellamkonda; Casey T. Tierney; Joseph J. Crisco; Derek A. Jones; Mireille E. Kelley; Jillian E. Urban; Joel D. Stitzel; Amaris Genemaras; Jonathan G. Beckwith; et al. (Annals of Biomedical Engineering, 2020)
Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions ( n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82–0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s 2 compared to 4412 ± 2326 rad/s 2 . These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Development of the STAR Evaluation System for Assessing Bicycle Helmet Protective Performance - Megan L. Bland; Craig McNally; David S. Zuby; Becky C. Mueller; Steven Rowson (Annals of Biomedical Engineering, 2020)

Repetitive Head Impact Exposure in College Football Following an NCAA Rule Change to Eliminate Two-A-Day Preseason Practices: A Study from the NCAA-DoD CARE Consortium - Brian D. Stemper; Alok S. Shah; Jaroslaw Harezlak; Steven Rowson; Stefan Duma; Jason P. Mihalik; Larry D. Riggen; Alison Brooks; Kenneth L. Cameron; Christopher C. Giza; Megan N. Houston; Jonathan Jackson; et al. (Annals of Biomedical Engineering, 2019)

Accounting for Variance in Concussion Tolerance Between Individuals: Comparing Head Accelerations Between Concussed and Physically Matched Control Subjects - Steven Rowson; Eamon T. Campolettano; Stefan M. Duma; Brian Stemper; Alok Shah; Jaroslaw Harezlak; Larry Riggen; Jason P. Mihalik; Kevin M. Guskiewicz; Christopher Giza; Alison Brooks; Kenneth Cameron; et al. (Annals of Biomedical Engineering, 2019)

Factors Affecting Head Impact Exposure in College Football Practices: A Multi-Institutional Study - Eamon T. Campolettano; Steven Rowson; Stefan M. Duma; Brian Stemper; Alok Shah; Jaroslaw Harezlak; Larry D. Riggen; Jason Mihalik; Alison Brooks; Kenneth Cameron; Christoper C. Giza; Thomas McAllister; et al. (Annals of Biomedical Engineering, 2019)

Comparison of Head Impact Exposure Between Concussed Football Athletes and Matched Controls: Evidence for a Possible Second Mechanism of Sport-Related Concussion - Brian D. Stemper; Alok S. Shah; Jaroslaw Harezlak; Steven Rowson; Jason P. Mihalik; Stefan M. Duma; Larry D. Riggen; Alison Brooks; Kenneth L. Cameron; Darren Campbell; John P. DiFiori; Christopher C. Giza; et al. (Annals of Biomedical Engineering, 2019)

Do Infield Softball Masks Effectively Reduce Facial Fracture Risk? - Tyler P. Morris; Ryan A. Gellner; Steven Rowson (Annals of Biomedical Engineering, 2019)

Estimated Brain Tissue Response Following Impacts Associated With and Without Diagnosed Concussion - Jonathan G. Beckwith; Wei Zhao; Songbai Ji; Amaris G. Ajamil; Richard P. Bolander; Jeffrey J. Chu; Thomas W. McAllister; Joseph J. Crisco; Stefan M. Duma; Steven Rowson; Steven P. Broglio; Kevin M. Guskiewicz; et al. (Annals of Biomedical Engineering, 2018)

Ranges of Injury Risk Associated with Impact from Unmanned Aircraft Systems - Eamon T. Campolettano; Megan L. Bland; Ryan A. Gellner; David W. Sproule; Bethany Rowson; Abigail M. Tyson; Stefan M. Duma; Steven Rowson (Annals of Biomedical Engineering, 2017)

Hockey STAR: A Methodology for Assessing the Biomechanical Performance of Hockey Helmets - Bethany Rowson; Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2015)

Head Impact Exposure in Youth Football: Elementary School Ages 9–12 Years and the Effect of Practice Structure - Bryan R. Cobb; Jillian E. Urban; Elizabeth M. Davenport; Steven Rowson; Stefan M. Duma; Joseph A. Maldjian; Christopher T. Whitlow; Alexander K. Powers; Joel D. Stitzel (Annals of Biomedical Engineering, 2013)

Brain Injury Prediction: Assessing the Combined Probability of Concussion Using Linear and Rotational Head Acceleration - Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2013)

The Virginia Tech Response - Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2012)

Head Impact Exposure in Youth Football - Ray W. Daniel; Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2012)

Rotational Head Kinematics in Football Impacts: An Injury Risk Function for Concussion - Steven Rowson; Stefan M. Duma; Jonathan G. Beckwith; Jeffrey J. Chu; Richard M. Greenwald; Joseph J. Crisco; P. Gunnar Brolinson; Ann-Christine Duhaime; Thomas W. McAllister; Arthur C. Maerlender (Annals of Biomedical Engineering, 2012)
Recent research has suggested a possible link between sports-related concussions and neurodegenerative processes, highlighting the importance of developing methods to accurately quantify head impact tolerance. The use of kinematic parameters of the head to predict brain injury has been suggested because they are indicative of the inertial response of the brain. The objective of this study is to characterize the rotational kinematics of the head associated with concussive impacts using a large head acceleration dataset collected from human subjects. The helmets of 335 football players were instrumented with accelerometer arrays that measured head acceleration following head impacts sustained during play, resulting in data for 300,977 sub-concussive and 57 concussive head impacts. The average sub-concussive impact had a rotational acceleration of 1230 rad/s 2 and a rotational velocity of 5.5 rad/s, while the average concussive impact had a rotational acceleration of 5022 rad/s 2 and a rotational velocity of 22.3 rad/s. An injury risk curve was developed and a nominal injury value of 6383 rad/s 2 associated with 28.3 rad/s represents 50% risk of concussion. These data provide an increased understanding of the biomechanics associated with concussion and they provide critical insight into injury mechanisms, human tolerance to mechanical stimuli, and injury prevention techniques.

Concussions Experienced by Major League Baseball Catchers and Umpires: Field Data and Experimental Baseball Impacts - Jeffrey A. Beyer; Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2012)

Validation of Concussion Risk Curves for Collegiate Football Players Derived from HITS Data - James R. Funk; Steven Rowson; Ray W. Daniel; Stefan M. Duma (Annals of Biomedical Engineering, 2012)

Development of the STAR Evaluation System for Football Helmets: Integrating Player Head Impact Exposure and Risk of Concussion - Steven Rowson; Stefan M. Duma (Annals of Biomedical Engineering, 2011)