Equestrian STAR: Development of an Experimental Methodology for Assessing the Biomechanical Performance of Equestrian Helmets - Lauren A. Duma; Mark T. Begonia; Barry Miller; Caitlyn Jung; Matthew Wood; Brock G. Duma; Steve Rowson (Annals of Biomedical Engineering, 2025)
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/s 2 . Between the linear-driven and oblique impacts, peak linear acceleration was weakly correlated ( R 2 = 0.34, p R 2 = 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.

Evaluating Polo Helmet Performance Across Different Impact Test Systems - Nicole E.-P. Stark; Mark T. Begonia; Steve Rowson (Annals of Biomedical Engineering, 2025)
Purpose This study evaluated head impact response between different helmet impact test systems by comparing the performance of ten polo helmets. Methods Helmets were evaluated using three test systems: a twin-wire guided drop tower, an oblique drop tower, and an impact pendulum. Impact tests were conducted at matched locations (front boss, side, rear boss) and speeds (3.46, 5.46 m/s). We employed a linear mixed model with helmet model as a random effect and calculated the least square mean differences between systems for peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and concussion risk. Correlations between systems by impact speed were explored, using linear models of each system as a function of the others, and calculated Spearman rank correlation coefficients between test systems for each dependent variable. Results Our results found distinct differences in PRA and concussion risk between the oblique and the pendulum impact systems due to the driving force. The acceleration range across helmet models was substantial, and responses differed between test systems at matched impact conditions. However, there were similarities between test systems in the rank order of helmet models. Head acceleration differences between helmets translated to larger differences in concussion risk between helmet models. Conclusion These trends provide a framework for comparing the headform’s response across varying loading conditions. When selecting a test system to evaluate helmets for a specific sport, it is essential to consider the relevant impact conditions and loading patterns to ensure that laboratory tests accurately represent real-world scenarios.

Quantifying Effects of Design Features on Youth Bicycle Helmet Performance During Oblique Impacts - Caitlyn Jung; Nicole E. -P. Stark; Susanna M. Gagliardi; Mark T. Begonia; Steve Rowson (Annals of Biomedical Engineering, 2025)
Purpose Cycling is a leading cause of youth sports-related head injury in the U.S. Although youth bicycle helmets sold in the U.S. comply with safety standards limiting head linear acceleration, there needs to be more information on relative differences in protection between helmets that pass. Additionally, studies have yet to look at quantifying youth bicycle helmet performance with respect to their design. Methods Twenty-one youth bicycle helmet models were subjected to oblique impacts at three locations and two impact speeds where peak linear acceleration (PLA) and peak rotational acceleration (PRA) were quantified. Design features were characterized, including expanded polystyrene (EPS) thickness and presence of shell protrusions. A linear mixed model was used to quantify the effects of design features on PLA and PRA. Results The youth bicycle helmet models evaluated produced wide ranges in kinematics across all configurations. PLA averaged 95.9 ± 26.1 g at 3.1 m/s and 170.1 ± 43.5 g at 5.2 m/s, while PRA averaged 3150 ± 1275 rad/s 2 at 3.1 m/s and 4990 ± 1977 rad/s 2 at 5.2 m/s. Impact location, impact speed, and EPS thickness had strong effects on PLA and PRA, whereas shell protrusions only had strong effects on PLA. Conclusion Youth bicycle helmets with thicker EPS, thinner shells, and shell protrusions at impact locations improved the linear and rotational kinematic measures. Limitations include the small sample size and the impacts analyzed not representing all possible real-world scenarios.

Uncalibrated Single-Camera View Video Tracking of Head Impact Speeds Using Model-Based Image Matching - Nicole E.-P. Stark; Ethan S. Henley; Brianna A. Reilly; John S. Nowinski; Gabrielle M. Ferro; Michael L. Madigan; Damon R. Kuehl; Steve Rowson (Annals of Biomedical Engineering, 2025)
Purpose This study evaluates the accuracy of a model-based image matching (MBIM) approach with model calibration for tracking head impact speeds in uncalibrated spaces from single-camera views. Methods Two validation datasets were used. The first included 36 videos of guided NOCSAE headform drops at varying camera positions (heights, distances, camera angles) where a speed gate measured vertical impact speed. The second dataset had eight videos of participants performing ladder falls with marked helmets, captured using a 12-camera motion capture system to track head impact speeds. Each video was tracked frame-by-frame, matching a 3D NOCSAE headform model to the head using MBIM software. Accuracy was assessed by comparing captured to MBIM-tracked speeds by the mean difference and Root Mean Square Error (RMSE). A linear model assessed the influence of camera position. Results For ideal camera views (90 degrees, height 1 or 1.4 m), MBIM-tracked vertical speeds were 0.04 ± 0.15 m/s faster than the true speed (RMSE 0.15 m/s; 2.3 ± 6.2% error). Across all 36 NOCSAE videos, MBIM-tracked vertical speeds were 0.03 ± 0.19 m/s faster (RMSE 0.19 m/s; 1.8 ± 6.9 % error). In participant videos, MBIM-tracked resultant speeds were 0.01 ± 0.33 m/s slower (RMES 0.31; 0.7 ± 9.5% error) compared to motion capture. Conclusion MBIM with model calibration can analyze head impact kinematics from single-camera footage without environment calibration, achieving reasonable accuracy compared to other systems. Analyzing head impact kinematics from uncalibrated single-camera footage presents significant opportunities for assessing previously untraceable videos.

Comparison of Instrumented Mouthguard Post-Processing Methods - Ryan Gellner; Mark T. Begonia; Matthew Wood; Lewis Rockwell; Taylor Geiman; Caitlyn Jung; Blake Gellner; Allison MacMartin; Sophia Manlapit; Steve Rowson (Annals of Biomedical Engineering, 2025)
Instrumented head acceleration measurement devices are commonly used in research studies to determine head acceleration exposure in certain populations. Instrumented mouthguards pair directly to the user’s teeth and offer six-degree-of-freedom measurements. Though many studies have recently used these devices, post-processing techniques vary by study. Other studies have attempted to label impact quality or coupling status, also with varying methods. This study sought to compare the effect of post-processing and labeling methods on reported exposure distribution characteristics in instrumented mouthguard data from ice hockey players. We collected data from 18 female adolescent ice hockey players on two teams for an entire season. We then post-processed the measured signals using five different techniques: (1) the instrumented mouthguard manufacturer’s data output, (2) a 500 Hz linear acceleration filter and a 300 Hz angular velocity filter, (3) HEADSport, (4) a 100 Hz linear acceleration filter and a 175 Hz angular velocity filter, and (5) a salvaging process to detect and remove decoupling based on signal frequency content. The post-processing techniques affected the reported exposure distributions by changing the mean, median, and 95th percentile values of peak linear and angular kinematics. We also compared labeling techniques by measuring agreement and inter-rater reliability between three labeling techniques: the instrumented mouthguard manufacturer’s label, Luke et al.’s coupling label, and our classification learner that detects and labels decoupling. We found that the labeling techniques had low agreement about which acceleration events were the best to keep. Labeling technique also influenced the reported distributions’ descriptive statistics. Post-processing and event labeling are crucial components of head acceleration event exposure studies. Methods should be described by researchers, and standardization should be sought to allow for better cross-study comparison. Published and publicly available techniques can help move the field toward this ideal. Researchers should be aware of the potential effect post-processing can have on a population’s final reported exposure metrics.

Detecting and Salvaging Head Impacts with Decoupling Artifacts from Instrumented Mouthguards - Ryan Gellner; Mark T. Begonia; Matthew Wood; Lewis Rockwell; Taylor Geiman; Caitlyn Jung; Blake Gellner; Allison MacMartin; Sophia Manlapit; Steve Rowson (Annals of Biomedical Engineering, 2025)
In response to growing evidence that repetitive head impact exposure and concussions can lead to long-term health consequences, many research studies are attempting to quantify the frequency and severity of head impacts incurred in various sports and occupations. The most popular apparatus for doing so is the instrumented mouthguard (iMG). While these devices hold greater promise of head kinematic accuracy than their helmet-mounted predecessors, data artifacts related to iMG decoupling still plague results. We recreated iMG decoupling artifacts in a laboratory test series using an iMG fit to a dentition mounted in a NOCSAE headform. With these data, we identified time, frequency, and time-frequency features of decoupled head impacts that we used in a machine learning classification algorithm to predict decoupling in six-degree-of-freedom iMG signals. We compared our machine learning algorithm predictions on the laboratory series and 80 video-verified field head acceleration events to several other proprietary and published methods for predicting iMG decoupling. We also present a salvaging method to remove decoupling artifacts from signals and reduce peak resultant error when decoupling is detected. Future researchers should expand these methods using on-field data to further refine and enable prediction of iMG decoupling during live volunteer use. Combining the presented machine learning model and salvaging technique with other published methods, such as infrared proximity sensing, advanced triggering thresholds, and video review, may enable researchers to identify and salvage data with decoupling artifacts that previously would have had to be discarded.

Correction: Optimising Instrumented Mouthguard Data Analysis: Video Synchronisation Using a Cross-correlation Approach - James Tooby; Steve Rowson; Kevin Till; David Allan; Melanie Dawn Bussey; Dario Cazzola; Éanna Falvey; Kenzie Friesen; Andrew J. Gardner; Cameron Owen; Gregory Roe; Thomas Sawczuk; et al. (Annals of Biomedical Engineering, 2025)

Optimising Instrumented Mouthguard Data Analysis: Video Synchronisation Using a Cross-correlation Approach - James Tooby; Steve Rowson; Kevin Till; David Allan; Melanie Dawn Bussey; Dario Cazzola; Éanna Falvey; Kenzie Friesen; Andrew J. Gardner; Cameron Owen; Gregory Roe; Thomas Sawczuk; et al. (Annals of Biomedical Engineering, 2025)
Purpose Head acceleration events (HAEs) are a growing concern in contact sports, prompting two rugby governing bodies to mandate instrumented mouthguards (iMGs). This has resulted in an influx of data imposing financial and time constraints. This study presents two computational methods that leverage a dataset of video-coded match events: cross-correlation synchronisation aligns iMG data to a video recording, by providing playback timestamps for each HAE, enabling analysts to locate them in video footage; and post-synchronisation event matching identifies the coded match event (e.g. tackles and ball carries) from a video analysis dataset for each HAE, this process is important for calculating the probability of match events resulting in HAEs. Given the professional context of iMGs in rugby, utilising commercial sources of coded match event datasets may expedite iMG analysis. Methods Accuracy and validity of the methods were assessed via video verification during 60 rugby matches. The accuracy of cross-correlation synchronisation was determined by calculating synchronisation error, whilst the validity of post-synchronisation event matching was evaluated using diagnostic accuracy measures (e.g. positive predictive value [PPV] and sensitivity). Results Cross-correlation synchronisation yielded mean synchronisation errors of 0.61–0.71 s, with all matches synchronised within 3 s’ error. Post-synchronisation event matching achieved PPVs of 0.90–0.95 and sensitivity of 0.99–1.00 for identifying correct match events for SAEs. Conclusion Both methods achieved high accuracy and validity with the data sources used in this study. Implementation depends on the availability of a dataset of video-coded match events; however, integrating commercially available video-coded datasets offers the potential to expedite iMG analysis, improve feedback timeliness, and augment research analysis.

On-Field Evaluation of Mouthpiece-and-Helmet-Mounted Sensor Data from Head Kinematics in Football - Ty D. Holcomb; Madison E. Marks; N. Stewart Pritchard; Logan E. Miller; Steve Rowson; Garrett S. Bullock; Jillian E. Urban; Joel D. Stitzel (Annals of Biomedical Engineering, 2024)
Purpose Wearable sensors are used to measure head impact exposure in sports. The Head Impact Telemetry (HIT) System is a helmet-mounted system that has been commonly utilized to measure head impacts in American football. Advancements in sensor technology have fueled the development of alternative sensor methods such as instrumented mouthguards. The objective of this study was to compare peak magnitude measured from high school football athletes dually instrumented with the HIT System and a mouthpiece-based sensor system. Methods Data was collected at all contact practices and competitions over a single season of spring football. Recorded events were observed and identified on video and paired using event timestamps. Paired events were further stratified by removing mouthpiece events with peak resultant linear acceleration below 10 g and events with contact to the facemask or body of athletes. Results A total of 133 paired events were analyzed in the results. There was a median difference (mouthpiece subtracted from HIT System) in peak resultant linear and rotational acceleration for concurrently measured events of 7.3 g and 189 rad/s 2 . Greater magnitude events resulted in larger kinematic differences between sensors and a Bland Altman analysis found a mean bias of 8.8 g and 104 rad/s 2 , respectively. Conclusion If the mouthpiece-based sensor is considered close to truth, the results of this study are consistent with previous HIT System validation studies indicating low error on average but high scatter across individual events. Future researchers should be mindful of sensor limitations when comparing results collected using varying sensor technologies.

Instrumented Mouthguard Decoupling Affects Measured Head Kinematic Accuracy - Ryan A. Gellner; Mark T. Begonia; Matthew Wood; Lewis Rockwell; Taylor Geiman; Caitlyn Jung; Steve Rowson (Annals of Biomedical Engineering, 2024)
Many recent studies have used boil-and-bite style instrumented mouthguards to measure head kinematics during impact in sports. Instrumented mouthguards promise greater accuracy than their predecessors because of their superior ability to couple directly to the skull. These mouthguards have been validated in the lab and on the field, but little is known about the effects of decoupling during impact. Decoupling can occur for various reasons, such as poor initial fit, wear-and-tear, or excessive impact forces. To understand how decoupling influences measured kinematic error, we fit a boil-and-bite instrumented mouthguard to a 3D-printed dentition mounted to a National Operating Committee on Standards for Athletic Equipment (NOCSAE) headform. We also instrumented the headform with linear accelerometers and angular rate sensors at its center of gravity (CG). We performed a series of pendulum impact tests, varying impactor face and impact direction. We measured linear acceleration and angular velocity, and we calculated angular acceleration from the mouthguard and the headform CG. We created decoupling conditions by varying the gap between the lower jaw and the bottom face of the mouthguard. We tested three gap conditions: 0 mm (control), 1.6 mm, and 4.8 mm. Mouthguard measurements were transformed to the CG and compared to the reference measurements. We found that gap condition, impact duration, and impact direction significantly influenced mouthguard measurement error. Error was higher for larger gaps and in frontal (front and front boss) conditions. Higher errors were also found in padded conditions, but the mouthguards did not collect all rigid impacts due to inherent limitations. We present characteristic decoupling time history curves for each kinematic measurement. Exemplary frequency spectra indicating characteristic decoupling frequencies are also described. Researchers using boil-and-bite instrumented mouthguards should be aware of their limitations when interpreting results and should seek to address decoupling through advanced post-processing techniques when possible.

Characterizing Natural Frequencies of the Hybrid III and NOCSAE Headforms - Kristin J. Dingelstedt; Steve Rowson (Annals of Biomedical Engineering, 2024)
The vibrational characteristics of the Hybrid III and NOCSAE headforms are not well understood. It is hypothesized that they may perform differently in certain loading environments due to their structural differences; their frequency responses may differ depending on the impact characteristics. Short-duration impacts excite a wider range of headform frequencies than longer-duration (padded) impacts. While headforms generally perform similarly during padded head impacts where resonant frequencies are avoided, excitation of resonant frequencies during short-duration impacts can result in differences in kinematic measurements between headforms for the matched impacts. This study aimed to identify the natural frequencies of each headform through experimental modal analysis techniques. An impulse hammer was used to excite various locations on both the Hybrid III and NOCSAE headforms. The resulting frequency response functions were analyzed to determine the first natural frequencies. The average first natural frequency of the NOCSAE headform was 812 Hz. The Hybrid III headform did not exhibit any natural frequencies below 1000 Hz. Comparisons of our results with previous studies of the human head suggest that the NOCSAE headform’s vibrational response aligns more closely with that of the human head, as it exhibits lower natural frequencies. This insight is particularly relevant for assessing head injury risk in short-duration impact scenarios, where resonant frequencies can influence the injury outcome.

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)

Human Head and Helmet Interface Friction Coefficients with Biological Sex and Hair Property Comparisons - Nicole E.-P. Stark; Charlotte Clark; Steve Rowson (Annals of Biomedical Engineering, 2024)
Dummy headforms used for impact testing have changed little over the years, and frictional characteristics are thought not to represent the human head accurately. The frictional interface between the helmet and head is an essential factor affecting impact response. However, few studies have evaluated the coefficient of friction (COF) between the human head and helmet surface. This study’s objectives were to quantify the human head’s static and dynamic COF and evaluate the effect of biological sex and hair properties. Seventy-four participants slid their heads along a piece of helmet foam backed by a fixed load cell at varying normal force levels. As normal force increased, static and dynamic human head COF decreased following power–law curves. At 80 N, the static COF is 0.32 (95% CI 0.30–0.34), and the dynamic friction coefficient is 0.27 (95% CI 0.26–0.28). Biological sex and hair properties were determined not to affect human head COF. The COFs between the head and helmet surface should be used to develop more biofidelic head impact testing methods, define boundary conditions for computer simulations, and aid decision-making for helmet designs.

Choosing Optimal Cutoff Frequencies for Filtering Linear Acceleration and Angular Velocity Signals Associated with Head Impacts Measured by Instrumented Mouthguards - Ryan Gellner; Mark Begonia; Steve Rowson (Annals of Biomedical Engineering, 2024)
Head impact sensors worn in the mouth are popular because they couple directly to the teeth and provide six-degree-of-freedom head measurements. Mouthpiece signal filters have conventionally used cutoff frequencies lower than recommended practices (Society of Automotive Engineers, SAE J211-1) to eliminate extraneous noise when measuring with live subjects. However, there is little information about the effects of filter choice on the accuracy of signals measured by instrumented mouthpieces. Lack of standardization in head impact measurement device post-processing techniques can result in data that are not comparable across studies or device brands. This study sought optimal filter cutoff frequencies for six-degree-of-freedom measurements made at the teeth using instrumented mouthguards. We collected linear acceleration and angular velocity signals at the head center of gravity (CG) using laboratory-grade instrumentation. We also collected and filtered similar six-degree-of-freedom measurements from an instrumented mouthguard using 24 cutoff frequencies, from 25 to 600 Hz. We transformed the measurements to linear acceleration at the center of gravity of the head (CG) using all kinematic variables at the teeth, optimizing linear and angular mouthguard cutoff frequencies with one equation. We calculated the percent error in transformed peak resultant linear acceleration and minimized the mean and standard deviation in error. The optimal cutoff frequencies were 175 Hz for linear acceleration and 250 Hz for angular velocity. Rigid impacts (3–5 ms duration) had higher optimal cutoff frequencies (175 Hz linear acceleration, 275 Hz angular velocity) than padded impacts (10–12 ms duration; 100 Hz linear acceleration, 175 Hz angular velocity), and all impacts together (3–12 ms duration; 175 Hz linear acceleration, 250 Hz angular velocity). Instrumented mouthpiece manufacturers and researchers using these devices should consider these optimal filter cutoff frequencies to minimize measurement error. Sport-specific filter criteria for teeth-based sensors may be warranted to account for the difference in optimal cutoff frequency combination by impact duration.

Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis - Steve Rowson; Jason Mihalik; Jillian Urban; Julianne Schmidt; Steve Marshall; Jaroslaw Harezlak; Brian D. Stemper; Mike McCrea; Jim Funk (Annals of Biomedical Engineering, 2022)
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.

Whitewater Helmet STAR: Evaluation of the Biomechanical Performance and Risk of Head Injury for Whitewater Helmets - Brock G. Duma; Mark T. Begonia; Barry Miller; Steve Rowson; Lauren A. Duma; Stefan M. Duma (Annals of Biomedical Engineering, 2022)

Football Shoulder Pad Design and Its Effect on Head Kinematics in Shoulder-to-Helmet Impacts - Zachary Wusk; Steve Rowson (Annals of Biomedical Engineering, 2022)

A Two-Phased Approach to Quantifying Head Impact Sensor Accuracy: In-Laboratory and On-Field Assessments - Emily E. Kieffer; Mark T. Begonia; Abigail M. Tyson; Steve Rowson (Annals of Biomedical Engineering, 2020)