Contact, collision, and combat sports have more head impacts as compared to noncontact sports; therefore, such sports are uniquely suited to the investigation of head impact biomechanics. Recent advances in technology have enabled the development of instrumented equipment, which can estimate the head impact kinematics of human subjectsin vivo. Literature pertaining to head impact measurement devices was reviewed and usage, in terms of validation and field studies, of such devices was discussed. Over the past decade, instrumented equipment has recorded millions of impacts in the laboratory, on the field, in the ring, and on the ice. Instrumented equipment is not without limitations; however,in vivohead impact data is crucial to investigate head injury mechanisms and further the understanding of concussion.

Background: Recent advances in technology have enabled the development of head impact sensors, which provide a unique opportunity for sports medicine researchers to study head kinematics in contact sports. Studies have suggested that video or observer confirmation of head impact sensor data is required to remove false positives. In addition, manufacturer filtering algorithms may be ineffective in identifying true positives and removing true negatives. Purpose: To (1) identify the percentage of video-confirmed events recorded by headband-mounted sensors in high school soccer through video analysis, overall and by sex; (2) compare video-confirmed events with the classification by the manufacturer filtering algorithms; and (3) quantify and compare the kinematics of true- and false-positive events. Study Design: Cohort study; Level of evidence, 2. Methods: Adolescent female and male soccer teams were instrumented with headband-mounted impact sensors (SIM-G; Triax Technologies) during games over 2 seasons of suburban high school competition. Sensor data were sequentially reduced to remove events recorded outside of game times, associated with players not on the pitch (ie, field) and players outside the field of view of the camera. With video analysis, the remaining sensor-recorded events were identified as an impact event, trivial event, or nonevent. The mechanisms of impact events were identified. The classifications of sensor-recorded events by the SIM-G algorithm were analyzed. Results: A total of 6796 sensor events were recorded during scheduled varsity game times, of which 1893 (20%) were sensor-recorded events associated with players on the pitch in the field of view of the camera during verified game times. Most video-confirmed events were impact events (n = 1316, 70%), followed by trivial events (n = 396, 21%) and nonevents (n = 181, 10%). Female athletes had a significantly higher percentage of trivial events and nonevents with a significantly lower percentage of impact events. Most impact events were head-to-ball impacts (n = 1032, 78%), followed by player contact (n = 144, 11%) and falls (n = 129, 10%) with no significant differences between male and female teams. The SIM-G algorithm correctly identified 70%, 52%, and 66% of video-confirmed impact events, trivial events, and nonevents, respectively. Conclusion: Video confirmation is critical to the processing of head impact sensor data. Percentages of video-confirmed impact events, trivial events, and nonevents vary by sex in high school soccer. Current manufacturer filtering algorithms and magnitude thresholds are ineffective at correctly classifying sensor-recorded events and should be used with caution.

Head impact sensors measure head kinematics in sports, and sensor accuracy is crucial for investigating the potential link between repetitive head loading and clinical outcomes. Many validation studies mount sensors to human head surrogates and compare kinematic measures during loading from a linear impactor. These studies are often unable to distinguish intrinsic instrumentation limitations from variability caused by sensor coupling. The aim of the current study was to evaluate intrinsic sensor error in angular velocity in the absence of coupling error for a common head impact sensor. Two Triax SIM-G sensors were rigidly attached to a preclinical rotational injury device and subjected to rotational events to assess sensor reproducibility and accuracy. Peak angular velocities between the SIM-G sensors paired for each test were correlated (R2 > 0.99, y = 1.00x, p < 0.001). SIM-G peak angular velocity correlated with the reference (R2 = 0.96, y = 0.82x, p < 0.001); however, SIM-G underestimated the magnitude by 15.0% ± 1.7% (p < 0.001). SIM-G angular velocity rise time (5% to 100% of peak) correlated with the reference (R2 = 0.97, y = 1.06x, p < 0.001) but exhibited a slower fall time (100% to 5% of peak) by 9.0 ± 3.7 ms (p < 0.001). Assessing sensor performance when rigidly coupled is a crucial first step to interpret on-field SIM-G rotational kinematic data. Further testing in increasing biofidelic conditions is needed to fully characterize error from other sources, such as coupling.

Previous studies of support legs in rearward-facing infant CRS models have focused on frontal impacts and have found that the presence of a support leg is associated with a reduction in head injury metrics. However, real-world crashes often involve an oblique principal direction of force. The current study used sled tests to evaluate the effectiveness of support legs in rearward-facing infant CRS models for frontal and frontal-oblique impacts with and without a simulated front row seatback. Frontal and frontal-oblique impact sled tests were conducted using the simulated Consumer Reports test method with and without the blocker plate, which was developed to represent a front row seatback. The Q1.5 anthropomorphic test device (ATD) was seated in rearward-facing infant CRS models, which were tested with and without support legs. The presence of a support leg was associated with significant reductions of head injury metrics below injury tolerance limits for all tests, which supports the findings of previous studies. The presence of a support leg was also associated with significant reductions of peak neck tensile force. The presence of the blocker plate resulted in greater head injury metrics compared to tests without the blocker plate, but the result was non-significant. However, the fidelity of the interaction between the CRS and blocker plate as an adequate representation of the interaction that would occur in a real vehicle is not well understood. The findings from the current study continue to support the benefit of support legs in managing the energy of impact for a child in a rearward-facing CRS.

Traumatic brain injury (TBI) and severe blood loss resulting in hemorrhagic shock (HS) are each leading causes of mortality and morbidity worldwide, and present additional treatment considerations when they are comorbid (TBI+HS) as a result of competing pathophysiological responses. The current study rigorously quantified injury biomechanics with high precision sensors and examined whether blood-based surrogate markers were altered in general trauma as well as post-neurotrauma. Eighty-nine sexually mature male and female Yucatan swine were subjected to a closed-head TBI+HS (40% of circulating blood volume; n = 68), HS only ( n = 9), or sham trauma ( n = 12). Markers of systemic (e.g., glucose, lactate) and neural functioning were obtained at baseline, and at 35 and 295 min post-trauma. Opposite and approximately twofold differences existed for both magnitude (device > head) and duration (head > device) of quantified injury biomechanics. Circulating levels of neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and ubiquitin C-terminal hydrolase L1 (UCH-L1) demonstrated differential sensitivity for both general trauma (HS) and neurotrauma (TBI+HS) relative to shams in a temporally dynamic fashion. GFAP and NfL were both strongly associated with changes in systemic markers during general trauma and exhibited consistent time-dependent changes in individual sham animals. Finally, circulating GFAP was associated with histopathological markers of diffuse axonal injury and blood–brain barrier breach, as well as variations in device kinematics following TBI+HS. Current findings therefore highlight the need to directly quantify injury biomechanics with head mounted sensors and suggest that GFAP, NfL, and UCH-L1 are sensitive to multiple forms of trauma rather than having a single pathological indication (e.g., GFAP = astrogliosis).