Laboratory and field evaluation of a small form factor head impact sensor in un-helmeted play

Abstract

Head impact sensors are increasingly used to quantify the frequency and magnitude of head impacts in sports. A dearth of information exists regarding head impact in un-helmeted sport, despite the substantial number of concussions experienced in these sports. This study evaluated the performance of one small form factor head impact sensor in both laboratory and field environments. In laboratory tests, sensor performance was assessed using a Hybrid III headform and neck. The headform assembly was mounted on a low-friction sled and impacted with three sports balls over a range of velocities (10-31 m/s) at two locations and from three directions. Measures of linear and angular acceleration obtained from the small form factor wireless sensor were compared to measures of linear and angular acceleration obtained by wired sensors mounted at the headform center of mass. Accuracy of the sensor varied inversely with impact magnitude, with relative differences across test conditions ranging from 0.1% to 266.0% for peak linear acceleration and 4.7% to 94.6% for peak angular acceleration when compared to a wired reference system. In the field evaluation, eight male high school soccer players were instrumented with the head impact sensor in seven games. Video of the games was synchronized with sensor data and reviewed to determine the number of false positive and false negative head acceleration event classifications. Of the 98 events classified as valid by the sensor, 20.5% (20 impacts) did not result from contact with the ball, another player, the ground or player motion and were therefore considered false positives. Video review of events classified as invalid or spurious by the sensor found 77.8% (14 of 18 impacts) to be due to contact with the ball, another player or player motion and were considered false negatives.

Comparison of head impact measurements via an instrumented mouthguard and an anthropometric testing device

“…The iMG sensors, sampling at 1 kHz (linear acceleration) and 952 Hz (rotational velocity), measured collision metrics comparable with those recorded by an ATD, sampling at 20 kHz, whilst utilising the pendulum-based impactor. Work conducted by Wu et al [64] and Nevins et al [65] have demonstrated the importance of sampling frequency as the duration of the impact decreases. Wu et al [64] investigated the effect of sample rate for wearable inertial sensors by dropping cadaver heads from a single height.…”

“…The authors highlighted that higher bandwidths are required for un-helmeted head impacts, recommending minimum accelerometer and gyroscope bandwidths of 500 Hz in unhelmeted sports conditions [64]. Nevins et al [65] produced ATD head accelerations with magnitudes ranging from 18.4 to 194.0 g, with the higher end achieved through impact velocities of 30 m/s and impact durations of 1-2 ms. They demonstrated that characterising the initial acceleration and rotation peaks, at a frequency of 1 kHz, will result in undersampling of the signal, potentially underestimating the true PLA and PRV values of the ATD headform.…”

Head Impact Sensor Studies In Sports: A Systematic Review Of Exposure Confirmation Methods

“…31 A wide variety of head impact sensors is currently available, such as instrumented helmets (e.g., GForceTracker), 5,7,26 headbands (e.g., SIM-G), 18,32,43 mouthguards (e.g., MIG) 16,46 and skin patches (e.g., xPatch). 23,28,33 Increasingly, research studies have used such technology to collect head impact data in sports, commonly American football. 30 Validation of kinematics recorded by head impact sensors in laboratory settings has typically used anthropometric test devices, 44 cadavers 17 and human volunteers.…”

“…47 Furthermore, field studies have evaluated the accuracy of sensors to measure head impact exposure using video analysis. 7,16,28,32,33 Such previous research has identified that the absence of observer and/or video confirmation of sensor-recorded events to remove false positives may result in substantial overestimation of head impact exposure. 7,18,32,33 Although filtering algorithms attempt to remove false positives in an automated fashion, some investigations suggest such approaches are limited and not a valid replacement for observer and/or video confirmation.…”

“…7,18,32,33 Although filtering algorithms attempt to remove false positives in an automated fashion, some investigations suggest such approaches are limited and not a valid replacement for observer and/or video confirmation. 28,32,33 Therefore, the absence of rigorous confirmation methods or use of a filtering algorithm may result in estimates of head impact exposure that are imprecise. To understand the prevalence of this issue in the literature, the purpose of the current systematic review was to determine the proportion of head impact sensor data studies published in the last two decades that used filtering algorithms, observer confirmation and/or video confirmation of sensor-recorded events to remove false positives.…”