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. Lead by Declan Patton, MD, along with Senior Author and PISC Senior Scholar, Kristy Arbogast, PhD, this study conducted 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. They reviewed the primary objective of each study 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