Parameter Studies and Optimization

The AnyBody Modeling System has a nice mechanism that allows you to perform investigations of the model’s reaction to its parameters and even to automatically find the set of parameters that causes a given behavior of the model. Some examples of applications are:

  • Systematic investigations of the model’s sensitivity to a group of parameters such as a muscle insertion point, muscle strength, or external support point.

  • Posture and movement prediction.

  • Optimization of muscular strength for a particular sports performance.

  • Optimization of the layout of a bicycle for a particular person.

  • Answering research questions such as: Could a T-rex jump? With optimization you can find the movement pattern that maximizes, for instance, the jump height given the body weight and limitations on muscular strength.


Parameter study: Metabolic efficiency of a bicycle as a function of seat height and seat horizontal position.

This functionality is provided through two complementary studies:

The AnyParamStudy performs an exhaustive search of the variable space computing the model’s reaction to every combination of the variables within a given interval. For instance, a parameter study could investigate the metabolic efficiency of a bicycle depending on the horizontal and vertical position of the saddle. The advantage of this study is that it gives you the ultimate overview of the system’s behavior. The disadvantage is that the number of computations grows exponentially with the number of parameters. A two-parameter problem with five values of each parameter leads to 5 x 5 = 25 analyses, which is usually no problem to do, while a five parameter problem will lead to 5^5 = 3125 analyses, which obviously is a more time-consuming undertaking, at least for larger models.

The AnyOptStudy performs a systematic search within a parameter space using optimization techniques of solutions that fulfill certain criteria. For instance, you could ask the study to find the saddle position that maximizes the metabolic efficiency of the bicycle while keeping the maximum muscle activity below a certain upper limit. The advantage of this study is that it does not need to compute al combinations of the parameters and therefore can handle spaces with multiple parameters within a reasonable time. The disadvantage is that it does not provide the overview of the design space that you get from a parameter study.

This tutorial devotes one lesson to each of the two study types:

  1. Defining a parameter study

  2. Optimization studies

See also

Next lesson: Defining a Parameter Study.