Anatomy Transfer

Characters with precise internal anatomy are important in film and visual effects, as well as in medical applications. We propose the first semi-automatic method for creating anatomical structures, such as bones, muscles, viscera and fat tissues. This is done by transferring a reference anatomical model from an input template to an arbitrary target character, only defined by its boundary representation (skin). The fat distribution of the target character needs to be specified. We can either infer this information from MRI data, or allow the users to express their creative intent through a new editing tool. The rest of our method runs automatically: it first transfers the bones to the target character, while maintaining their structure as much as possible. The bone layer, along with the target skin eroded using the fat thickness information, are then used to define a volume where we map the internal anatomy of the source model using harmonic (Laplacian) deformation. This way, we are able to quickly generate anatomical models for a large range of target characters, while maintaining anatomical constraints

Synthesis of Subject-Specific Human Balance Responses using a Task-Level Neuromuscular Control Platform

Many activities of daily living require a high level of neuromuscular coordination and balance control to avoid falls. Complex musculoskeletal models paired with detailed neuromuscular simulations complement experimental studies and uncover principles of coordinated and uncoordinated movements. Here, we created a closed-loop forward dynamic simulation framework that utilizes a detailed musculoskeletal model (19 degrees of freedom, and 92 Muscles) to synthesize human balance responses after support-surface perturbation. In addition, surrogate response models of task-level experimental kinematics from two healthy subjects were provided as inputs to our closedloop simulations to inform the design of the task-level controller. The predicted muscle EMGs and the resulting synthesized subject joint angles showed good conformity with the average of experimental trials. The simulated whole-body center of mass displacements, generated from a single kinematics trial per perturbation direction, were on average, within 7 mm (anterior perturbations) and 13 mm (posterior perturbations) of experimental displacements. Our results confirmed how a complex subject-specific movement can be reconstructed by sequencing and prioritizing multiple task-level commands to achieve desired movements. By combining the multidisciplinary approaches of robotics and biomechanics, the platform demonstrated here offers great potential for studying human movement control and subject-specific outcome prediction

Functionality-Driven Musculature Retargeting

We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and joint range of motion while preserving the functionality of the original musculature as closely as possible. The geometric configuration and physiological parameters of musculotendon units are estimated and optimized to adapt to new bodies. The range of motion around joints is estimated from a motion capture dataset and edited further for individual models. The retargeted model is simulation-ready, so we can physically simulate muscle-actuated motor skills with the model. Our system is capable of generating a wide variety of anatomical bodies that can be simulated to walk, run, jump and dance while maintaining balance under gravity. We will also demonstrate the construction of individualized musculoskeletal models from bi-planar X-ray images and medical examinations.Comment: 15 pages, 20 figure

Comparison of Several Muscle Modeling Alternatives for Computationally Intensive Algorithms in Human Motion Dynamics

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Several approaches are currently employed to address the predictive simulation of human motion, having in common their high computational demand. Muscle modeling seems to be an essential ingredient to provide human likeness to the obtained movements, at least for some activities, but it increases even more the computational load. This paper studies the efficiency and accuracy yielded by several alternatives of muscle modeling in the forward-dynamics analysis of captured motions, as a method that encompasses the computationally intensive character of predictive simulation algorithms with a known resulting motion which simplifies the comparisons. Four muscle models, the number of muscles, muscle torque generators, muscular synergies, and look-up tables for musculotendon lengths and moment arms are considered and analyzed, seeking to provide criteria on how to include the muscular component in human multibody models so that its effect on the resulting motion is captured while keeping a reasonable computational cost. Gait and vertical jump are considered as examples of slow- and fast-dynamics motions. Results suggest that: (i) the rigid-tendon model with activation dynamics offers a good balance between accuracy and efficiency, especially for short-tendon muscles; (ii) including muscles in the model leads to a decrease in efficiency which is highly dependent on the muscle model employed and the number of muscles considered; (iii) muscle torque generators keep the efficiency of skeletal models; (iv) muscular synergies offer almost no advantage for this problem; and (v) look-up tables for configuration-dependent kinematic magnitudes have a non-negligible impact on the efficiency, especially for simplified muscle models.Open Access funding provided by Universidade da Coruña/CISUG thanks to the CRUE-CSIC agreement with Springer Natur