Annals of Biomedical Engineering- 12.2.20
Minneapolis, MN – In an attempt to quantify the accuracy of commercially available head impact monitoring systems, top researchers at Virginia Tech recently performed a study to evaluate the laboratory and on-field performance of these systems.
As noted in their review, “although there are many head impact sensors available, skepticism on their utility exists over concerns related to measurement error. Previous studies report mixed reliability in head impact sensor measurements, but there is no uniform approach to assessing accuracy, making comparisons between sensors and studies difficult.”
With this in mind, Virginia Tech researchers laid out a two-phase approach to evaluating head impact sensor accuracy. “The first phase consists of in-lab impact testing on a dummy headform at varying impact severities under loading conditions representative of each sensor’s intended use. We quantify in-lab accuracy by calculating the concordance correlation coefficient (CCC) between a sensor’s kinematic measurements and headform reference measurements. For sensors that performed reasonably well in the lab (CCC ≥ 0.80), we completed a second phase of evaluation on-field.”
Out of the eight sensors evaluated, only four sensors passed the in-lab accuracy requirements set forth. Once the in-lab accuracy testing was completed, the researchers moved on to evaluating the sensors in an on-field environment. “The purpose of on-field testing was to determine how well the sensor performs during real-world conditions. The reason this type of testing is needed beyond laboratory testing is that the sensor coupling to the head may deviate from the in-lab coupling conditions.”
For the on-field evaluation of the Prevent system, 15 collegiate men’s rugby players were instrumented for a total of 41 athlete sessions. This in-depth onfield evaluation found that Prevent was the most reliably accurate on-field system among its peers. “The Prevent IMM is an example of a sensor that performed well in the lab (high CCC) and the real-world (high PPV), leading us to think that it is an overall accurate system.”
The research conducted by Virginia Tech outlines the importance of accuracy as it relates to measuring and reporting head impacts. In order for head impact data to truly be actionable, the user must be able to trust the data they are receiving. When it comes down to the health & safety of athletes, bad data is worse than no data at all.
