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  • PhD Defense - Danyong Zhao

    Tue, Oct 12, 2021 @ 04:00 PM - 06:00 PM

    Computer Science

    University Calendar


    PhD candidate: Dangyong Zhao

    Committee:
    Jernej Barbic (Chair)
    C.-C. Jay Kuo
    Yong Chen

    Date and Time: 10/12 at 4pm


    Acquisition of Human Tissue Elasticity Properties Using Pressure Sensors


    Abstract:

    Physically based simulation of the human body in three dimensions is important in many applications in computer graphics, animation, virtual reality, virtual commerce, ergonomics and virtual medicine. Finite Element Method (FEM) is a robust and reliable approach to simulate deformable dynamics of three-dimensional elastic structures. However, for quality simulation that matches the behavior of real human tissues, FEM needs accurate material properties that correctly model real relationships between the strains and stresses in the human tissue. This thesis presents methods to capture such nonlinear materials for the human musculo-skeletal tissue (skin, fat, muscles) in vivo, through carefully designed poking experiments, force meters, lasers and ultrasound measuring devices. From our experiments, we obtain ground-truth relationships between the contact force and skin deformation. We then fit material models that best approximate the acquired real-world data.



    First, we design a measuring device that can simultaneously capture the skin contact force and the skin deformation, consisting of a force meter and a laser distance measuring device. We design sliding and pivoting joints to rigidly attach the force meter to the laser device, so that diverse human body locations (arm, hand, belly, etc.) can be measured ergonomically and reliably. We also use an ultrasound device to capture the depth of the human subcutaneous fat at different locations; enabling us to generate a 3d model of the fat layer, and optionally also the muscle layer, of the human body.



    Second, we propose a novel approach to equivalently convert 3D FEM simulations into 2D simulation, suitable for our material capture. This method permits us to greatly speed up our material optimizations, without losing any accuracy. We validated this approach by comparing the simulation result from 2D equations and the 3D traditional equations. We propose to use natural cubic splines to parameterize the three separable scalar elastic energy density functions based on the Valanis-Landel material model. Based on our novel 2D simulation method and the spline-based non-linear isotropic material, we present an efficient method to compute the gradient of the objective function for optimization and use the conjugate gradient optimization method to optimize the material.



    Lastly, we use our acquired materials to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically based contact between the surface and a deformable human. We model the soft deformable human using a layer of FEM deformable tissue surrounding a rigid core, with measured realistic elastic material properties, and large-deformation nonlinear analysis using our material capturing and optimizing method. We define a novel cost function to measure the ergonomics of contact between the human and the supporting surface. We give a stable and computationally efficient contact model that is differentiable with respect to the supporting surface shape. This makes it possible to optimize our ergonomic cost function using gradient-based optimizers. We 3D-print the optimized shoe sole, measure contact pressure using pressure sensors, and demonstrate that the real unoptimized and optimized pressure distributions qualitatively match those predicted by our simulation.



    WebCast Link: https://usc.zoom.us/j/94230145329

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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