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Repeatability and Biofidelity of a Physical Surrogate Neck Model Fit to a Hybrid III Head

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Abstract

In helmet impact testing, parameters including acceleration and velocity are measured using instrumented head-neck models that are meant to be mechanically realistic (i.e. biofidelic) stand-ins, or surrogates, for humans. Currently available models of the human neck are designed primarily for application in automotive crash testing, and their applicability in assessment of helmets is often questioned. The object of the present work is to document the mechanical design, repeatability, and biofidelity in low speed impact of a new neck model that we apply with a Hybrid III head. Focusing on Hybrid III head kinematics measured during impacts at 2 to 6 m/s, the co-efficient of variance of repeated measures of kinematics was generally less than 10%. Differences in kinematics between identical copies of the neck was less than 20% when tested with helmets, and less than 7% when the head was not helmeted. In parallel testing using a Hybrid III head-neck, the co-efficient of variance in repeated measures was less than 4% and the kinematics significantly differed from those measured using the new neck. CORAplus scores for the new neck were approximately 0.70 when compared against data for human subjects with passive neck muscles experiencing impact at 2 m/s.

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Acknowledgments

The authors wish to acknowledge the equal contributions of the three lead authors on this manuscript.

Funding

Financial support for the following is gratefully acknowledged from several sources: The Natural Sciences and Engineering Research Council of Canada (Discovery and Engage Grants); The Canada Foundation for Innovation; The Canada Research Chairs Program; and the Faculty of Engineering at the University of Alberta.

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Correspondence to Gabriella Wynn.

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Associate Editor Joel Stitzel oversaw the review of this article.

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MacGillivray, S., Wynn, G., Ogle, M. et al. Repeatability and Biofidelity of a Physical Surrogate Neck Model Fit to a Hybrid III Head. Ann Biomed Eng 49, 2957–2972 (2021). https://doi.org/10.1007/s10439-021-02786-z

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