Background : There have been several advancements in modelling the behaviour of the finger and its internal anatomical structures and in the development of anthropomorphic fingers. Most studies that include ligaments focus on force distribution in the tendon-ligament network for a particular task. In the design of anthropomorphic fingers, especially in two recent projects, ligament attachments have been decided through iterative trials and the the tendon network has been used to control the range of motion of the finger. However, the collateral ligaments also play a major role in limiting the range of motion of the finger in addition to contributing to medial-lateral joint stability.
Aim : The aim of this project is to develop an algorithm to automatically compute coordinates for collateral ligament attachment sites for the Distal Inter-Phalangeal (DIP) joint of the finger, given a required range of motion in terms of maximum flexion and extension angles.
Method : The DIP joint was described in two dimensions (in the sagittal plane) with one degree of freedom (flexion-extension). Constraints were formulated based on geometry and observed and reported ligament length ranges. The model formulation was also informed by insights from the dissection of three preserved human index fingers. The algorithm named ’Auto-LINC’ (Automating Ligament Insertion Coordinates) involved two stages. The first was a combinatorial approach used to establish the best possible combination of attachment sites out of a set of feasible solutions. This was used to seed the second stage - a continuous domain approach used for local optimisation. The algorithm was designed in such a way that the two stages can be used separately or in combination depending on the application.
Results : The attachment sites computed using the combined approach were used to add ligaments to an existing OpenSim simulation model of an anthropomorphic DIP joint to verify that the required range of motion was achieved. The process was illustrated with an example in which 99.6% of the required range of motion was achieved using ligaments with attachment sites computed by Auto-LINC.
Discussion : The use of an algorithm with geometric constraints and objective function yielded feasible solutions in a short time. By adapting the constraints to suit differences in geometry, Auto-LINC
can also be used to predict collateral ligament attachment sites for other flexion-extension joints such as the Proximal Inter-Phalangeal (PIP) joint. Auto-LINC has potential for use in the design of anthropomorphic fingers as it automates the process of deciding ligament attachment sites. It also has potential for use in guiding robot-assisted reconstruction surgery. It can be made more detailed and versatile by adding material properties and constitutive equations and by extension into three dimensions.
Conclusion : Auto-LINC is already usable in its current form to compute form based on function, and has potential for use in automating anthropomorphic design and guiding reconstruction surgery. In
contrast to other published research, Auto-LINC computes ligament attachment sites based on range of motion - in other words, it focuses on moving from function to form rather than form to function.