Head-Impact–Measurement Devices: A Systematic Review

Abstract

Context: With an estimated 3.8 million sport-and recreation-related concussions occurring annually, targeted prevention and diagnostic methods are needed. Biomechanical analysis of head impacts may provide quantitative information that can inform both prevention and diagnostic strategies.Objective: To assess available head-impact devices and their clinical utility.Data Sources: We performed a systematic search of the electronic database PubMed for peer-reviewed publications, using the following phrases: accelerometer and concussion, head impact telemetry, head impacts and concussion and sensor, head impacts and sensor, impact sensor and concussion, linear acceleration and concussion, rotational acceleration and concussion, and xpatch concussion. In addition to the literature review, a Google search for head impact monitor and concussion monitor yielded 15 more devices.Study Selection: Included studies were performed in vivo, used commercially available devices, and focused on sportrelated concussion.Data Extraction: One author reviewed the title and abstract of each study for inclusion and exclusion criteria and then reviewed each full-text article to confirm inclusion criteria. Controversial articles were reviewed by all authors to reach consensus.Data Synthesis: In total, 61 peer-reviewed articles involving 4 head-impact devices were included. Participants in boxing, football, ice hockey, soccer, or snow sports ranged in age from 6 to 24 years; 18% (n ¼ 11) of the studies included female athletes. The Head Impact Telemetry System was the most widely used device (n ¼ 53). Fourteen additional commercially available devices were presented.Conclusions: Measurements collected by impact monitors provided real-time data to estimate player exposure but did not have the requisite sensitivity to concussion. Proper interpretation of previously reported head-impact kinematics across age, sport, and position may inform future research and enable staff clinicians working on the sidelines to monitor athletes. However, head-impact-monitoring systems have limited clinical utility due to error rates, designs, and low specificity in predicting concussive injury.

Development of a Concussion Risk Function for a Youth Population Using Head Linear and Rotational Acceleration

“…Further, 95th percentile values are more representative of the magnitudes for head impacts typically associated with injury. 32,42 Risk-weighted exposure is an aggregate measure that combines impact frequency and magnitude as a means of considering overall head impact exposure. 12,40,42,53 The risk of concussion was computed for each head impact sustained by an athlete, and then these individual risk values were summed together into one measure.…”

Elevated markers of brain injury as a result of clinically asymptomatic high-acceleration head impacts in high-school football athletes

“…However, the ability to implement the use of biomechanical data that predict concussion remains elusive. 19,25 Nevertheless, high-acceleration head impacts (HHIs) have consistently been shown to elevate the risk of neurological injury. 6 In a study of 54,247 head impacts captured by helmet accelerometry in high-school athletes, there was a 6.9% incidence of mTBI when the impact exceeded 5582.6 rad/sec 2 in rotational acceleration and 96.1g in linear acceleration, while the incidence of mTBI was 0.00004% when the impact magnitude fell below these values.…”

Preliminary evidence from a prospective DTI study suggests a posterior‐to‐anterior pattern of recovery in college athletes with sports‐related concussion

“…Collectively, these studies agree that peak strains and stresses of concussive injury are located near the brainstem in central brain areas such as the midbrain, thalamus, and corpus callosum regardless of the actual head impact location. However, research has also suggested that head impact sensors do not yet have the sensitivity needed to accurately locate the impact azimuth or determine a reliable g‐force threshold for concussion diagnosis (Allison, Kang, Bolte, Maltese, & Arbogast, ; Guskiewicz & Mihalik, ; King, Hume, Gissane, Brughelli, & Clark, ; Kutcher et al, ; O'Connor, Rowson, Duma, & Broglio, ). For example, a study seeking to quantify head impact exposure for a collegiate women's soccer team over the course of a season found that head impact sensor data had both a high level of false positives and false negatives when compared to video analysis of potential concussive hits and a medical assessment of concussive injury (Press & Rowson, ).…”