Reconstruction of 3D tooth images

Proceedings - International Conference on Image Processing, ICIP51077-108

An Efficient Biomechanical Tongue model for Speech Research

Abstract. We describe our investigation of a fast 3D finite element method (FEM) for biomedical simulation of a muscle-activated human tongue. Our method uses a linear stiffness-warping scheme to achieve simulation speeds which are within a factor 10 of real-time rates at the expense of a small loss in accuracy. Muscle activations are produced by an arrangement of forces acting along selected edges of the FEM geometry. The model’s dynamics are integrated using an implicit Euler formulation, which can be solved using either the conjugate gradient method or a direct sparse solver. To assess the utility of this model, we compare its accuracy against slower, but less approximate, simulations of a reference tongue model prepared using the FEM simulation package ANSYS

The Distributed Lambda (λ) Model (DLM): A 3-D, Finite-Element Muscle Model Based on Feldman's λ Model; Assessment of Orofacial Gestures

International audiencePurpose: The authors aimed to design a distributed Lambda model (DLM), which is well-adapted to implement three-dimensional (3-D) Finite Element descriptions of muscles. Method: A muscle element model was designed. Its stress-strain relationships included the active force-length characteristics of the Lambda model along the muscle fibers, together with the passive properties of muscle tissues in the 3-D space. The muscle element was first assessed using simple geometrical representations of muscles in form of rectangular bars. Then, it was included in a 3-D face model, and its impact on lip protrusion was compared with the impact of a Hill-type muscle model. Results: The force-length characteristic associated with the muscle elements matched well with the invariant characteristics of the Lambda model. The impact of the passive properties was assessed. Isometric force variation and isotonic displacements were modeled. The comparison with a Hill-type model revealed strong similarities in terms of global stress and strain. Conclusion: The DLM accounted for the characteristics of the Lambda model. Biomechanically no clear differences were found between the DLM and a Hill-type model. Accurate evaluations of the Lambda model, based on the comparison between data and simulations, are now possible with 3-D biomechanical descriptions of the speech articulators because to the DLM

sEMG-assisted inverse modelling of 3D lip movement: a feasibility study towards person-specific modelling

We propose a surface-electromyographic (sEMG) assisted inverse-modelling (IM) approach for a biomechanical model of the face to obtain realistic person-specific muscle activations (MA) by tracking movements as well as innervation trajectories. We obtained sEMG data of facial muscles and 3D positions of lip markers in six volunteers and, using a generic finite element (FE) face model in ArtiSynth, performed inverse static optimisation with and without sEMG tracking on both simulation data and experimental data. IM with simulated data and experimental data without sEMG data showed good correlations of tracked positions (0.93 and 0.67) and poor correlations of MA (0.27 and 0.20). When utilising the sEMG-assisted IM approach, MA correlations increased drastically (0.83 and 0.59) without sacrificing performance in position correlations (0.92 and 0.70). RMS errors show similar trends with an error of 0.15 in MA and of 1.10 mm in position. Therefore, we conclude that we were able to demonstrate the feasibility of an sEMG-assisted inverse modelling algorithm for the perioral region. This approach may help to solve the ambiguity problem in inverse modelling and may be useful, for instance, in future applications for preoperatively predicting treatment-related function los