Laboratory Reconstructions of Concussive Helmet-to-Helmet Impacts in the National Football League.

Journal Article (Clinical Trial;Journal Article)

Seventeen concussive helmet-to-helmet impacts occurring in National Football League (NFL) games were analyzed using video footage and reconstructed by launching helmeted crash test dummies into each other in a laboratory. Helmet motion on-field and in the laboratory was tracked in 3D before, during, and after impact in multiple high frame rate video views. Multiple (3-10) tests were conducted for each of the 17 concussive cases (100 tests total) with slight variations in input conditions. Repeatability was assessed by duplicating one or two tests per case. The accuracy of the input conditions in each reconstruction was assessed based on how well the closing velocity, impact locations, and the path eccentricity of the dummy heads matched the video analysis. The accuracy of the reconstruction output was assessed based on how well the changes in helmet velocity (translational and rotational) from the impact matched the video analysis. The average absolute error in helmet velocity changes was 24% in the first test, 20% in the tests with the most accurate input configuration, and 14% in the tests with minimal error. Coefficients of variation in 22 repeated test conditions (1-2 per case) averaged 3% for closing velocity, 7% for helmet velocity changes, and 8% for peak head accelerations. Iterative testing was helpful in reducing error. A combination of sophisticated video analysis, articulated physical surrogates, and iterative testing was required to reduce the error to within half of the effect size of concussion.

Full Text

Duke Authors

Cited Authors

  • Funk, JR; Jadischke, R; Bailey, A; Crandall, J; McCarthy, J; Arbogast, K; Myers, B

Published Date

  • November 2020

Published In

Volume / Issue

  • 48 / 11

Start / End Page

  • 2652 - 2666

PubMed ID

  • 33000448

Electronic International Standard Serial Number (EISSN)

  • 1573-9686

International Standard Serial Number (ISSN)

  • 0090-6964

Digital Object Identifier (DOI)

  • 10.1007/s10439-020-02632-8

Language

  • eng