PIPER  1.0.1
PIPER Modules Overview

Table of Contents

List of modules currently integrated

The following modules are available in the application:

  • Pre-Process
  • Scale
    • Anthropo Module : estimates anthropometric dimensions based on a set of predictors (scaling)
    • Scaling Constraint Module : allows building a correspondence between anthropometric dimensions and a HBM to prepare scaling, and calls the Kriging module to transform the HBM (scaling)
  • Position
    • Pre-Positioning Module : pre-position the PIPER model using an interactive physics-based simulation (positioning)
    • Fine-Positioning Module : position the HBM using physics-based simulation (refinement of pre-position) (positioning)
  • Post-Process
    • Smoothing module : tool to improve the quality of the HBM by smoothing the mesh or the transformation (post-process)
  • Tools
    • Kriging Module : transforms the HBM using Kriging interpolation and sets of control points (tool)
    • Contour Deformation Module : tool to transform the HBM using contour based approaches (tool, scaling, positioning)
    • Shaping Module : tool to shape the flesh of you HBM using a set of point handles (beta version)
    • Scaling Parameter Module : tool to modify model parameters (tool, post-process)
  • Custom

Several modules are typically used (chained) to perform a transformation. An overview of the articulation of the modules and functionalities for positioning and scaling is provided below. A few examples of workflows are also provided in the Workflow Examples.

modules_overview.png
Overview of the articulation of the modules

Scaling in PIPER: overview

HBM Scaling approaches seem more widespread in the literature than positioning approaches. The PIPER framework provides several tools than greatly can help with HBM scaling mainly based on anthropometric dimensions or landmarks (unfortunately, no module using Statistical Shape Models could be integrated yet) The main modules provided include:

  • a module to estimates anthropometric dimensions based on a set of predictors (Anthropo Module) and three public anthropometric databases from children to elderly. A functionality to predict anthropometric dimensions directly using the GEBOD regression is also included.
  • the Scaling Constraint Module to build interactively correspondences between anthropometric dimensions and a HBM to prepare scaling. The module can also call all required modules to define the target and perform the transformation
  • a geometrical interpolation module to support model morphing (Kriging Module). The module integrates many numerical features useful within the context of HBM scaling (allows arbitrary number of control points, automatic control point decimation, weighting of the bone and skin, use of surface distance...)
  • a module (Scaling the PIPER child model by age) dedicated to the PIPER Child scaling with age, which allows generating easily models by selecting and age or stature started (based on the GEBOD regressions). The functionality to scale the material parameters with age is also included as an experimental feature.
  • a Contour Deformation Module to transform the HBM using contour based approaches

Positioning in PIPER: overview

Positioning finite element Human Body Models (HBM) for safety is a challenging task. To the contrary of dummies, applying a succession of rotations and translations is not possible because the HBM includes non robotic joints with complex articular contacts because soft tissues need to be deformed along. Because of this, HBM positioning is typically performed by finite element simulation. These can be time consuming to set up and to run. Beyond that, the properties of the HBM were typically selected for their response at high acceleration levels and may not be appropriate for physiological motion or low deceleration. Furthermore, postural preferences and muscular reactions also affect the posture .

The PIPER framework aims to propose some alternative methodologies that can be used along current approaches. Positioning in PIPER typically starts with the Pre-Positioning Module (or pre-positioning). The HBM is automatically transformed into a simplified model with a limited number of degrees of freedom that can be used in physics-based interactive simulation. Despite being simplified and interactive, the simulation can among others account for collisions between bones (to prevent penetration, limit range of motion, ...) and provide a rough transformation of the soft tissues.

The pre-positioning process is the place where the user can input its various constraints, weight them, and compute a plausible posture (for the skeleton in particular). Constraints could also include a priori knowledge such as physiological observations or postural preferences which are not classical mechanical parameters. For now, physiological descriptions of the spinal curvature (called Spine controller) can interact with the model (e.g. collision detection on the vertebrae) during postural change.

Several options are then possible to transform the HBM using this pre-position as the target:

  • the Fine-Positioning Module : the pre-positioning motion can be repeated (using the constraints or the bone positions) with finer parameters for the simulation. While more time consuming (for the initialization in particular), it can provide a more plausible deformation of the flesh.
  • the Contour Deformation Module can be applied using the bony landmarks from the preposition as a target. It can also be used independently
  • the pre-position can be used to generate a finite element simulation input (though a python script, an example being provided) and a full finite element simulation can be run.

In all cases, the use of the Transformation smoothing after positioning was found to greatly improve the results. In some cases (for smaller motion), the pre-position may be directly used and lead to a plausible and runnable model after smoothing.

In all cases, smoothing functionalities can be used to improve the HBM quality (Smoothing module).