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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.

IMPORTANCE Concussion diagnosis remains clinical, without objective diagnostic tests available for adolescents. Known deficits in visual accommodation and autonomic function after concussion make the pupillary light reflex (PLR) a promising target as an objective physiological biomarker for concussion.OBJECTIVE To determine the potential utility of PLR metrics as physiological biomarkers for concussion.DESIGN, SETTING, AND PARTICIPANTS Prospective cohort of adolescent athletes between ages 12 and 18 years recruited between August 1, 2017, and December 31, 2018. The study took place at a specialty concussion program and private suburban high school and included healthy control individuals (n = 134) and athletes with a diagnosis of sport-related concussion (SRC) (n = 98). Analysis was completed June 30, 2020. EXPOSURES Sports-related concussion and pupillometry assessments.MAIN OUTCOMES AND MEASURES Pupillary light reflex metrics (maximum and minimum pupillary diameter, peak and average constriction/dilation velocity, percentage constriction, and time to 75% pupillary redilation [T75]).RESULTS Pupillary light reflex metrics of 134 healthy control individuals and 98 athletes with concussion were obtained a median of 12.0 days following injury (interquartile range [IQR], 5.0-18.0 days). Eight of 9 metrics were significantly greater among athletes with concussion after Bonferroni correction (maximum pupil diameter: 4.83 mm vs 4.

To further the understanding of long-term sequelae as a result of repetitive head impacts in sports, in vivo head impact exposure data are critical to expand on existing evidence from animal model and laboratory studies. Recent technological advances have enabled the development of head impact sensors to estimate the head impact exposure of human subjects in vivo. Previous research has identified the limitations of filtering algorithms to process sensor data. In addition, observer and/or video confirmation of sensor-recorded events is crucial to remove false positives. The purpose of the current study was to conduct a systematic review to determine the proportion of published head impact sensor data studies that used filtering algorithms, observer confirmation and/or video confirmation of sensor-recorded events to remove false positives. Articles were eligible for inclusion if collection of head impact sensor data during live sport was reported in the methods section. Descriptive data, confirmation methods and algorithm use for included articles were coded. The primary objective of each study was reviewed to identify the primary measure of exposure, primary outcome and any additional covariates. A total of 168 articles met the inclusion criteria, the publication of which has increased in recent years. The majority used filtering algorithms (74%). The majority did not use observer and/or video confirmation for all sensor-recorded events (64%), which suggests estimates of head impact exposure from these studies may be imprecise.

Wearable sensors that accurately record head impacts experienced by athletes during play can enable a wide range of potential applications including equipment improvements, player education, and rule changes. One challenge for wearable systems is their ability to discriminate head impacts from recorded spurious signals. This study describes the development and evaluation of a head impact detection system consisting of a mouthguard sensor and machine learning model for distinguishing head impacts from spurious events in football games. Twenty-one collegiate football athletes participating in 11 games during the 2018 and 2019 seasons wore a custom-fit mouthguard instrumented with linear and angular accelerometers to collect kinematic data. Video was reviewed to classify sensor events, collected from instrumented players that sustained head impacts, as head impacts or spurious events. Data from 2018 games were used to train the ML model to classify head impacts using kinematic data features (127 head impacts; 305 non-head impacts). Performance of the mouthguard sensor and ML model were evaluated using an independent test dataset of 3 games from 2019 (58 head impacts; 74 non-head impacts). Based on the test dataset results, the mouthguard sensor alone detected 81.6% of video-confirmed head impacts while the ML classifier provided 98.3% precision and 100% recall, resulting in an overall head impact detection system that achieved 98.3% precision and 81.6% recall.

ObjectivesTo examine sex differences in sport-related concussion (SRC) across comparable sports.MethodsProspective cohort of collegiate athletes enrolled between 2014 and 2017 in the Concussion Assessment, Research and Education Consortium study.ResultsAmong 1071 concussions (females=615; 57.4%), there was no difference in recovery (median days to full return to play) (females=13.5 (IQR 9.0, 23.1) vs males=11.8 (IQR 8.1, 19.0), p=0.96). In subgroup analyses, female recovery was longer in contact (females=12.7 days (IQR 8.8, 21.4) vs males=11.0 days (IQR 7.9, 16.2), p=0.0021), while male recovery was longer in limited contact sports (males=16.9 days (IQR 9.7, 101.7) vs females=13.8 days (IQR 9.1, 22.0), p<0.0001). There was no overall difference in recovery among Division I schools (females=13.7 (IQR 9.0, 23.1) vs males=12.2 (IQR 8.2 19.7), p=0.5), but females had longer recovery at the Division II/III levels (females=13.0 (IQR 9.2, 22.7) vs males=10.6 (IQR 8.1, 13.9), p=0.0048).ConclusionOverall, no difference in recovery between sexes across comparable women’s and men’s sports in this collegiate cohort was found. However, females in contact and males in limited contact sports experienced longer recovery times, while females had longer recovery times at the Division II/III level. These disparate outcomes indicate that, while intrinsic biological sex differences in concussion recovery may exist, important, modifiable extrinsic factors may play a role in concussion outcomes.

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Associate Editor Stefan M Duma oversaw the review of this article.