A Numerical Model of the Human Ankle/Foot under Impact Loading in Inversion and Eversion 962428

Since numerous years, the vehicle industry is interested in occupant safety. The dummy use in crash tests allowed to create protective means like the belt and the airbag that diminished the injuries of the head and the thorax, which are often lethal for the car occupant. An other objective appears now: to improve the car safety to avoid the injuries which are not fatal but which can cause disability and which cause great cost in hospitalization and rehabilitation. The lower extremity protection, in particular the one of the ankle and the foot region, has become the subject of diverse research efforts by its high percentage of injuries in car crashes. But the dummy mechanics cannot reproduce the accurate ankle and the foot kinematics during an impact loading like in vehicle crash. Therefore, ankle/foot complex numerical models are an essential tool for the car safety improvement.

The simulation of the ankle dorsiflexion response during an impact loading was presented in a first paper ([1]). The influence of a few parameters of the biological components modeling was studied in a second paper ([2]).

The present paper presents the simulation of the other principal movements in car crash: the inversion and the eversion. In order to validate the ankle/foot model, the experimental tests of Professor Begeman presented in [6] are chosen. At first, the ankle/foot model with rigid bones is validated at different levels of energy. The gross kinematics of the model is correlated with the experimental tests. At a local level, the main relative motions of the bones during the inversion and the eversion were found in the simulation.

For inversion, the paper also compares the calculated forces and moments at the point of fixation at mid-length of the leg with test results, the quality of which indicates future directions of improvements of the model.

The future work will validate the model with deformable bones in the case of inversion and eversion. Both models will be validated also in static cases.