Biomechanical models are composed of linked segments. A segment is typically a skeletal bone (e.g. the femur) or set of bones (e.g. the foot). Each segment has
defined end points and a defined orientation
a geometrical shape (cylinder, cone, sphere, ellipsoid, or custom variation)
mass (based on textbook averages unless overridden)
length (calculated from the end points)
associated visual object to aid visualization (in Alias Wavefront object format or VRML)
The program considers any two segments in proximity to be "linked" and references a Joint between them.
A skeletal model is comprised of a collection of 6 degree of freedom segments. The six degrees of freedom of a rigid body can be determined by the specification of three non-collinear targets attached to the segment. A biomechanical model comprises the relative location of all of the segments defined in the model of the system and a method for determining the connections between adjacent segments; in other words, a way to define the location of the joint centers, for which forces are transmitted between segments.
At the core of Visual3D is the development of a flexible biomechanical modeling tool that can be used to define an unrestricted number of rigid segments and link them together in a cohesive fashion. Model Builder is the process for defining the segments based on target (MoCap marker) data collected by a motion capture system. Visual3D requires that there is a static trial that is used to define a local coordinate system for each segment (Segment Coordinate System). The Segment Coordinate System is defined explicitly by 3 or 4 non-colinear markers (real or virtual) that provide anatomically meaningful orientations. A set of 3 or more markers attached to the rigid segment is used to track the movement of the segment and at each frame of data specify the pose (position and orientation) of the segment.
The pose (postion and orientation) of each segment is calculated using an optimal method. This is contrasted with many software packages that compute segment coordinate systems on a frame-by-frame basis resulting in inconsistencies throughout the data. The use of optimal strategies is perhaps the most important attribute of the Visual3D model. Optimal strategies are described in more detail in the literature. (Terminology from Cappello, A., Cappozzo, A., La Palombara, P.F., Lucchetti, L., Leardini, A. Multiple anatomical landmark calibration for optimal bone pose estimation. Human Movement Science. 16: 259- 274, 1997). This is opposed to non-optimal methods, such as those used in the VCM software by Vicon.
Model Builder allows the you to analyze any collection of movement data, enabling the study upper torso gestures (wheelchair locomotion, pointing and throwing motions) or head movements. Assistive devices, or moving transducers, can be incorporated into the biomechanical analysis. The user has the ultimate control over the linking of rigid segments and structures.
The process of building a segment defines the transformation from the recorded markers to the pose of the biomechanical model, to the pose of a transducer (force plate or force transducer) or to the pose of an assistive device. The strategy for defining the Local Coordinate System (LCS) for a segment was derived from the strategy developed by Tom Kepple at the National Institutes of Health and incorporated into NIH MOVE3D. This strategy has been refined dramatically by the inclusion of LANDMARKS, which extends the functionality of 6 degree of freedom modeling.
Each segment requires at least three calibration markers (TARGETS or LANDMARKS) that are used to locate the proximal and distal ends of the segment and define the frontal plane of the LCS. The significance of this strategy lies in the fact that LANDMARKS can be created in a wide variety of ways, which allows Visual3D to mimic the models created by any marker configuration protocol whether traditional to gait analysis (e.g. Helen Hayes), or custom made in a laboratory. This has proved to be extremely useful for clinics or laboratories that are switching (or have switched) from one hardware vendor to another.
An evolving feature of Visual3d is the ability to perform kinematic and kinetic calculations on non-optimal marker configurations such as those used routinely by many laboratories. Visual3D, therefore, will accomodate legacy data that a laboratory may have archived that was collected using a non-optimal marker configuration.
A Visual3D model consists of a set of rigid segments, each of which corresponds to a body segment (major bone structure) of the subject whose motion is under study. We use the terms model segment and body segment when it is necessary to distinguish between the conceptual/mathematical segments of a Visual3D model and the corresponding physical body segments of the subject. Most of the time, we will simply say ”r;segment” when the distinction is clear from context.
The instantaneous position and orientation of all a segment is called the pose of the segment. The central function of Visual3D is translation of the target-marker positions (as reported by the motion-tracking apparatus) into the pose of the corresponding model. Two factors complicate this process:
The motion-tracking apparatus does not track segments; it
tracks target markers attached to various chosen points on or near the
subject’s body.
Segments are defined by (among other things) their proximal and distal
end points, which are located inside the body, but target markers can
generally only be placed outside the body.
To deal with the first complication, Visual3D makes use of the notion of segment-relative coordinate systems (usually called simply segment coordinate systems or SCS). The idea is that although the motion-tracking apparatus reports marker positions by their laboratory or LCS coordinates, and in general all markers are moving, it can safely be assumed that the target markers move with the body segments to which they are attached, i.e., each target’s coordinates in the appropriate segment coordinate system (SCS) do not change throughout the movement. Provided at least three target markers, not positioned in a line, are tracked for each body segment, Visual3D will have enough information to determine the model pose.
To deal with the second complication, Visual3D allows you to define the precise spatial relationships between each segment’s proximal and distal endpoints and the positions of target markers. This process is normally facilitated by capturing the position of extra calibration markers placed at points which, though not suitable for use in motion tracking, provide clear information about the location of joint centers within the body. Note that the choice of where and how to place target markers is itself a significant subject.
The illustration above shows what you might see when defining just one segment—the right thigh. The graphic image, which is zoomed in to the right thigh region, reveals three calibration markers (yellow) which are used to define the thigh segment’s endpoints and dimensions. At the proximal (upper) end, the RHP (right hip) marker’s position is used together with an explicit radius of 0.081m (measured in the laboratory for this subject) to define the proximal endpoint. At the distal end, both medial and lateral knee markers (RMK, RLK) are available, and together define both the distal endpoint and the distal radius of the thigh segment. For mass- and moment-related computations, this segment is modeled as a truncated cone (this is one of many details you provide under the Segment Properties tab) and so both proximal and distal radii are needed.