--- a
+++ b/Docs/Applications/Mocap/BVH_OptimizeOrigin.md
@@ -0,0 +1,40 @@
+---
+gallery_title: "Optimize BVH Origin"
+gallery_image: "/Applications/images/BVH_OptimizeOrigin_Merged.jpg"
+---
+
+(sphx_glr_auto_examples_Mocap_plot_BVH_OptimizeOrigin.py)=
+
+(examples_mocap_bvhorigin)=
+
+# Optimize BVH Origin example
+
+
+````{sidebar} **Example**
+<img src="/Applications/images/BVH_OptimizeOrigin_Merged.jpg" width="70%" align="center">
+````
+
+Example of a MoCap model using data from an inertial motion capture suit.
+The model uses a BVH file with data from an Xsens suit. The ground reaction
+forces are predicted using the GRF prediction algorithm.
+
+
+```{admonition} **Main file location in AMMR:**
+:class: seealso
+{menuselection}`Application --> MocapExamples --> BVH_Xsens_OptimizeOrigin --> Subjects --> S1 --> S01_Trial01 --> Main.any`
+```
+
+This particular example demonstrates a class template that can be used to optimize the origin of the
+BVH recording. The class template can be useful when BVH recordings consist of interaction of the subject
+with environment objects. In such trials, it can be hard to locate the environment object relative to
+the subject. The origin of the BVH model (recording) can be set to another position and orientation with
+respect to the Global Ref. This class template can optimize the origin of the BVH model such that a
+target segment of the human model (Left/Right Foot/Hand) hits a known position and orientation in a
+given time interval while following the recorded motion from the trial.
+
+
+Normally, in BVH models, AnyBody automatically calculates the virtual markers positions, and the model is scaled directly from
+the size of the BVH stick figure. Hence the model contains no *Parameter identification* step to find the parameters.
+In this model for optimizing the origin, the parameter identification step must be run manually prior
+to running the model.
+