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ABSTRACT -

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test. The second objective was to investigate age-related injury risks by performing a frontal US NCAP simulation test with the GHBMC M50 65 YO and the GHBMC M50 v4.2 models. Simulation results were compared to the GHBMC M50 v4.2 to evaluate the effect of age on occupant response and risk for head injury, neck injury, thoracic injury, and lower extremity injury. Overall, the GHBMC M50 65 YO model predicted higher probabilities of AIS 3+ injury for the head and thorax.

KEYWORDS - Older occupant, Injury risk, Finite element modeling, Full human body model

INTRODUCTION

Morphologic, compositional, and material changes in the human body with age can result in increased fragility and frailty in the elderly as well as an elevated incidence of injury and increased risk of mortality and morbidity (Bürstein et al. 1976; Zioupos and Currey 1998; Kahane 2013). In the next 40 years, the United States is projected to experience a rapid growth in the elderly population, with the proportion of adults aged 65+ years in the population increasing from 13% in 2010 to 20% by 2040 (Vincent and Velkoff 2010). By 2050, the population of persons aged 65+ years is projected to reach 16% globally and 26% in more developed countries (Haub 2011; U.S. Census Bureau 2013). The growing elderly population presents a need for full human body computational models that are representative of explicitly older occupants. Such models can...

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