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Laboratory Validation of Two Wearable Sensor Systems for Measuring Head Impact Severity in Football Players

Overview of attention for article published in Annals of Biomedical Engineering, August 2015
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Title
Laboratory Validation of Two Wearable Sensor Systems for Measuring Head Impact Severity in Football Players
Published in
Annals of Biomedical Engineering, August 2015
DOI 10.1007/s10439-015-1420-6
Pubmed ID
Authors

Gunter P. Siegmund, Kevin M. Guskiewicz, Stephen W. Marshall, Alyssa L. DeMarco, Stephanie J. Bonin

Abstract

Wearable sensors can measure head impact frequency and magnitude in football players. Our goal was to quantify the impact detection rate and validity of the direction and peak kinematics of two wearable sensors: a helmet system (HITS) and a mouthguard system (X2). Using a linear impactor, modified Hybrid-III headform and one helmet model, we conducted 16 impacts for each system at 12 helmet sites and 5 speeds (3.6-11.2 m/s) (N = 896 tests). Peak linear and angular accelerations (PLA, PAA), head injury criteria (HIC) and impact directions from each device were compared to reference sensors in the headform. Both sensors detected ~96% of impacts. Median angular errors for impact directions were 34° for HITS and 16° for X2. PLA, PAA and HIC were simultaneously valid at 2 sites for HITS (side, oblique) and one site for X2 (side). At least one kinematic parameter was valid at 2 and 7 other sites for HITS and X2 respectively. Median relative errors for PLA were 7% for HITS and -7% for X2. Although sensor validity may differ for other helmets and headforms, our analyses show that data generated by these two sensors need careful interpretation.

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Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 208 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 34 16%
Student > Ph. D. Student 33 16%
Student > Master 25 12%
Researcher 19 9%
Student > Doctoral Student 14 7%
Other 26 12%
Unknown 59 28%
Readers by discipline Count As %
Engineering 48 23%
Sports and Recreations 25 12%
Medicine and Dentistry 20 10%
Neuroscience 11 5%
Nursing and Health Professions 8 4%
Other 25 12%
Unknown 73 35%