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Development of the STAR Evaluation System for Football Helmets: Integrating Player Head Impact Exposure and Risk of Concussion

Overview of attention for article published in Annals of Biomedical Engineering, May 2011
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Title
Development of the STAR Evaluation System for Football Helmets: Integrating Player Head Impact Exposure and Risk of Concussion
Published in
Annals of Biomedical Engineering, May 2011
DOI 10.1007/s10439-011-0322-5
Pubmed ID
Authors

Steven Rowson, Stefan M. Duma

Abstract

In contrast to the publicly available data on the safety of automobiles, consumers have no analytical mechanism to evaluate the protective performance of football helmets. The objective of this article is to fill this void by introducing a new equation that can be used to evaluate helmet performance by integrating player head impact exposure and risk of concussion. The Summation of Tests for the Analysis of Risk (STAR) equation relates on-field impact exposure to a series of 24 drop tests performed at four impact locations and six impact energy levels. Using 62,974 head acceleration data points collected from football players, the number of impacts experienced for one full season was translated to 24 drop test configurations. A new injury risk function was developed from 32 measured concussions and associated exposure data to assess risk of concussion for each impact. Finally, the data from all 24 drop tests is combined into one number using the STAR formula that incorporates the predicted exposure and injury risk for one player for one full season of practices and games. The new STAR evaluation equation will provide consumers with a meaningful metric to assess the relative performance of football helmets.

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Mendeley readers

The data shown below were compiled from readership statistics for 301 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
United Kingdom 1 <1%
Turkey 1 <1%
New Zealand 1 <1%
Canada 1 <1%
Unknown 294 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 23%
Student > Bachelor 51 17%
Student > Master 46 15%
Researcher 30 10%
Student > Doctoral Student 20 7%
Other 45 15%
Unknown 40 13%
Readers by discipline Count As %
Engineering 108 36%
Medicine and Dentistry 35 12%
Sports and Recreations 33 11%
Agricultural and Biological Sciences 19 6%
Psychology 13 4%
Other 30 10%
Unknown 63 21%