The rates of fatality and injured persons of elderly people are gradually increasing in automotive accidents in Japan. In particular, elderly female occupants are most susceptible to injuries, especially on thorax and head-neck regions, based on previous studies using automotive accident data. This study developed a finite element (FE) model of 5th percentile female (AF05) with multiple muscles, and applied it to investigation on the injury mechanisms of elderly female occupants.

Individual muscle models of whole body with passive and active properties were integrated with an AF05 FE model that we developed previously. Material properties of skeletal parts with low strength of elderly people and smaller physiological cross-sectional area (PCSA) of each muscle of elderly females were obtained from the literature and commercially available image data, and were inputted to the model. Smaller PCSA of each muscle in elderly females would generate less muscular forces than younger males while less stiff bone properties of elderly females would generate more bone fractures than younger males. The developed elderly AF05 model without muscle activation was firstly validated against some cadaver test data on frontal impacts for the thorax and abdomen, and head-neck responses during a low-speed rear-end collision, and were compared with young adult 50th percentile male (AM50) model with multiple muscles that we developed previously. The simulation results of the elderly AF05 model generally showed good agreement with test data.

The elderly AF05 model was secondly used for investigation on effect of muscle activation to thoracic deformation in frontal impact situations with belt and hub loadings, and head-neck response in a low-speed rear impact situation. In the simulations on the thoracic deformation, a bracing condition was assumed and an activation level of 20% was assumed for all muscles in the trunk. Simulation results showed that the maximum thoracic deflections of the elderly AF05 model without muscle activation were two times and three times larger than those of young adult AM50 model with muscle activation in belt and hub loadings, respectively. From comparison between the elderly AF05 model and the young adult AM50 model, lower strength of bones and smaller PSCA of each muscle in the elderly AF05 model could increase thoracic deflection. In the simulation on the head-neck response, activation level of each muscle during a low-speed rear impact was estimated using a controller of multiple muscles with reinforcement learning (RL) that we developed previously. Simulation results showed that the maximum head angular velocity of the elderly AF05 model was larger than that of the young adult AM50 model, especially in considering muscle activation. The elderly AF05 could not prevent the head from rotating rearward due to their weak muscular forces.

Although the elderly AF05 model has some limitations on lack of experimental data for validations and estimation of muscle activation, it has the potential for better understanding of injury mechanisms of elderly female occupants.