— FE Model

MIPS has access to a state of the art 3D numerical model of the human head, developed by Professor Svein Kleiven at Sweden’s Royal Institute of Technology (KTH). This computational model represents the most critical parts of the human head, including the skull, brain and other tissues, and relies upon the finite element method (FEM), a numerical method widely used when building houses, bridges or simulating car crashes. At MIPS, we use the head FE model to simulate helmeted head impacts and to evaluate the risk of different types of head injuries.

Why is a numeric model used?

In a helmet test, the instrumented head form will measure the linear and angular accelerations. And while we could use the acceleration pulses to predict the risk for a brain injury, the strain commuted by the FE model has shown to better predict to the risk of a brain injury than the acceleration-based criteria.

How is it used?

The model incorporates 50.000 elements connected with nodes (think “LEGO”, except in a computer program), allowing us to apply acceleration pulses to the elements representing the skull in the model. The FE software (LSDYNA) will then compute the strain (Deformation) in each element representing the brain.


When applying an acceleration pulse to the head model, the brain will deform in different patterns depending on the impact direction and impact pulse. Our interest is in the strain that has shown to correlate well to the risk of a brain injury, like concussion.

Which results can you get from this model and how reliable are they?

We use the FE model when we test the same model of helmet with, and without MIPS BPS. By comparing the brain strain induced by the FE model in both helmet versions, we can be sure that when we see the MIPS BPS-equipped helmet reducing stress on the brain, the results are accurate and repeatable.


The FE model developed at KTH in Stockholm is exceedingly robust. A product of twenty person-years of time investment, it is used by twenty scientific publications and has even predicted the precise location of brain injury in real-world accident reconstructions.