BioBuddy is an open-source tool for translating, creating and personalizing musculoskeletal models across different formats (e.g., .osim, .bioMod). By enabling reliable interoperability between modeling environments, BioBuddy allows researchers to focus on scientific questions rather than technical constraints.

How to install

Currently, the only way to install BioBuddy is from source. But it will be available on conda-forge and pip in the near future.

If you are a user, you can set up your environment with minimal dependencies.

conda install -c conda-forge python=3.11.11 pip
pip install scipy==1.15.1 numpy==1.25.2 lxml ezc3d

Note: On mac, you might need to add conda install conda-forge::libcxx

However, if you are a developer and want to contribute, you will need to set up your environment using the following command: Due to the OpenSim dependency used only in BioBuddy's tests, we recommend using python=3.11.

pip install pytest pytest-cov codecov
conda install -c opensim-org opensim=4.5.1
conda install -c conda-forge biorbd=1.11.2 deepdiff

Model translation

You can load the original model using one of the BiomechanicalModelReal().from_[format] methods, and then export it into another format using the BiomechanicalModelReal.to_[format] method (see example).

from biobuddy import BiomechanicalModelReal

# Read an .osim file
model = BiomechanicalModelReal().from_osim(
    filepath=osim_filepath,
    # Other optional parameters here
)

# Translate it into a .bioMod file
model.to_biomod(biomod_filepath)

Model creation

A model can also be created from scratch using the BiomechanicalModel. In this generic model, everything can be defined through functions (i.e., without numerical values). The subject specific model (a BiomechanicalModelReal) can then be generated by evaluating the generic model with a motion capture trial. This feature is especially useful for kinematic models where the joint centers are defined based on anatomical marker placement (like in the plug in gait, see full example).

Here is a simple example of how to add components to such a model:

# Create the model
model = BiomechanicalModel()
de_leva = DeLevaTable(total_mass=60, sex=Sex.FEMALE)

# Add components to build the kinematic chain
model.add_segment(
    Segment(
        name="HEAD",
        parent_name="TRUNK",
        segment_coordinate_system=SegmentCoordinateSystem(
            "BOTTOM_HEAD",
            first_axis=Axis(name=Axis.Name.Z, start="BOTTOM_HEAD", end="HEAD_Z"),
            second_axis=Axis(name=Axis.Name.X, start="BOTTOM_HEAD", end="HEAD_XZ"),
            axis_to_keep=Axis.Name.Z,
        ),
        mesh=Mesh(("BOTTOM_HEAD", "TOP_HEAD", "HEAD_Z", "HEAD_XZ", "BOTTOM_HEAD")),
        inertia_parameters=de_leva[SegmentName.HEAD],
    )
)
model.segments["HEAD"].add_marker(Marker("BOTTOM_HEAD"))
model.segments["HEAD"].add_marker(Marker("TOP_HEAD"))
model.segments["HEAD"].add_marker(Marker("HEAD_Z"))
model.segments["HEAD"].add_marker(Marker("HEAD_XZ"))

# Evaluate the model with a motion capture trial
model_real = model.to_real(C3dData(c3d_filepath))

There are many different components available to build a model (see this example to see how to add those components to your model).

Model personalization

The current version of BioBuddy allows you to modify your BiomechanicalModelReal to personalize it to your subjects by:

• Scaling
• Identifying joint centers

Scaling:

The scaling is performed by the ScaleTool which can be initialized from scratch like this:

original_model = BiomechanicalModelReal()

# Create the scaling configuration
scaling_configuration = ScaleTool(original_model)

# Add a scaling segment for the pelvis
scaling_configuration.add_scaling_segment(
    SegmentScaling(
        name="pelvis",
        scaling_type= SegmentWiseScaling(
            axis=Translations.XYZ,
            marker_pairs=[
                ["RASIS", "LASIS"],
                ["RPSIS", "LPSIS"],
            ]
        )
    )
)

# Add marker weights for the pelvis segment
scaling_configuration.add_marker_weight(MarkerWeight(name="RASIS", weight=1.0))
scaling_configuration.add_marker_weight(MarkerWeight(name="LASIS", weight=1.0))
scaling_configuration.add_marker_weight(MarkerWeight(name="RPSIS", weight=0.5))
scaling_configuration.add_marker_weight(MarkerWeight(name="LPSIS", weight=0.5))

or by reading from an existing file (e.g., .xml or .biomod) using the appropriate ScaleTool.from_[format] method. Once the scaling configuration is set up, you can scale your model based on a static trial (.c3d file) and the total mass of your participant using the ScaleTool.scale like this:

# Performing the scaling based on a static trial
scale_tool = ScaleTool.from_biomod(biomod_filepath)
scaled_model = scale_tool.scale(static_c3d=C3dData(filepath), mass=mass)

For now, there are three scaling methods available:

• BodyWiseScaling: scales the entire body based on the total height of the participant.
• SegmentWiseScaling: scales the segment based on the distance between marker pairs.
• AxisWiseScaling: scales each axis of the segment independently based on the distance between marker pairs.

Joint center identification:

The JointCenterTool allows you to identify the joint centers of your model based on the movement of segments during functional trials. First, you need to define the joint center configuration using JointCenterTool.add() method to define the joint you want to modify. Then, you can use the JointCenterTool.replace_joint_centers() method to modify each joint.

from biobuddy import JointCenterTool

# Set up the joint center identification tool
joint_center_tool = JointCenterTool(scaled_model)
# Example for the right hip
joint_center_tool.add(
    Score(
        functional_c3d=C3dData(c3d_filepath, first_frame=100, last_frame=900),
        parent_name="pelvis",
        child_name="femur_r",
        parent_marker_names=["RASIS", "LASIS", "LPSIS", "RPSIS"],
        child_marker_names=["RGT", "RUB_Leg", "RUF_Leg", "FBF_Leg", "RMFE", "RLFE"],
    )
)
# Example for the right knee
joint_center_tool.add(
    Sara(
        functional_c3d=C3dData(c3d_filepath),
        parent_name="femur_r",
        child_name="tibia_r",
        parent_marker_names=["RGT", "RUB_Leg", "RUF_Leg", "FBF_Leg"],
        child_marker_names=["RATT", "RUB_Tib", "RDF_Tib", "RDB_Tib", "RSPH", "RLM"],
    )
)

# Perform the joint center identification
modified_model = joint_center_tool.replace_joint_centers()

For now, two algorithms were implemented SCoRE to locate the position of the joint center and SARA to identify the joint axis of rotation. Please note that in both cases, all segment components stay the same, only the joint position and axis are modified.

Note

Understandably, not all modeling formats have the same functionalities, so some features may not be available for all formats. We will try to keep here a list up to date of the features that are available in BioBuddy that are not available for each format:

• biorbd (.bioMod):
  • PathPointCondition is not implemented yet in biorbd. So if your BioBuddy model has this component, we recommend running BiomechanicalModelReal.fix_via_points(q) before BiomechanicalModelReal.to_biomod(path). This will evaluate the via point conditions at the desired posture (which should be close to the range of motion during the movement studied). If the condition is not meet, the via point is inactive, so it is removed from the model. Please note that this is a destructive operation, once the conditions are evaluated, they are removed from the model and the remaining via points are fixed on the segments.
  • PathPointMovement are not implemented yet in biorbd. So if your BioBuddy model has this components, we recommend running BiomechanicalModelReal.fix_via_points(q) before BiomechanicalModelReal.to_biomod(path). This will fix the position of the moving via points, muscle origin, and muscle insertion by evaluating the position function at the desired posture (which should be close to the range of motion during the movement studied). Please note that this is a destructive operation, once the movements are evaluated, they are removed from the model and the remaining via points are fixed on the segments.

How to cite

@software{biobuddy_2025,
  author       = {Eve Charbonneau, Pierre Puchaud, Teddy Caderby, Mickael Begon, Amedeo Ceglia, Benjamin Michaud},
  title        = {Bringing the musculoskeletal modeling community together with BioBuddy},
  month        = april,
  year         = 2025,
  publisher    = {submitted to Congrès de la Société de biomécanique},
  url          = {https://github.com/pyomeca/biobuddy}
}

How to contribute

Our goal is to support as many musculoskeletal model formats as possible, so do not hesitate to contact us if you'd like to see your favorite format supported by BioBuddy. If you are using BioBuddy and encounter any problem, please open an issue on this GitHub repository. We are also open to suggestions for new features or improvements to existing functionality. All contributions are welcome!