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优化粘弹性有限元模型以模拟干燥、自然状态和湿润的人体手指按压玻璃的情况。

Optimizing a Viscoelastic Finite Element Model to Represent the Dry, Natural, and Moist Human Finger Pressing on Glass.

作者信息

Nam Saekwang, Kuchenbecker Katherine J

出版信息

IEEE Trans Haptics. 2021 Apr-Jun;14(2):303-309. doi: 10.1109/TOH.2021.3077549. Epub 2021 Jun 17.

Abstract

When a fingerpad presses into a hard surface, the development of the contact area depends on the pressing force and speed. Importantly, it also varies with the finger's moisture, presumably because hydration changes the tissue's material properties. Therefore, we collected data from one finger repeatedly pressing a glass plate under three moisture conditions, and we constructed a finite element model that we optimized to simulate the same three scenarios. We controlled the moisture of the subject's finger to be dry, natural, or moist and recorded 15 pressing trials in each condition. The measurements include normal force over time plus finger-contact images that are processed to yield gross contact area. We defined the axially symmetric 3D model's lumped parameters to include an SLS-Kelvin model (spring in series with parallel spring and damper) for the bulk tissue, plus an elastic epidermal layer. Particle swarm optimization was used to find the parameter values that cause the simulation to best match the trials recorded in each moisture condition. The results show that the softness of the bulk tissue reduces as the finger becomes more hydrated. The epidermis of the moist finger model is softest, while the natural finger model has the highest viscosity.

摘要

当指尖压在坚硬表面上时,接触面积的形成取决于压力和速度。重要的是,它还会随手指的湿度而变化,推测是因为水合作用改变了组织的材料特性。因此,我们收集了同一根手指在三种湿度条件下反复按压玻璃板的数据,并构建了一个有限元模型,对其进行优化以模拟相同的三种情况。我们将受试者手指的湿度控制为干燥、自然或湿润,并在每种条件下记录15次按压试验。测量包括随时间变化的法向力以及经过处理以得出总接触面积的手指接触图像。我们定义了轴对称三维模型的集总参数,包括用于主体组织的一个SLS-开尔文模型(串联弹簧与并联弹簧和阻尼器),以及一个弹性表皮层。使用粒子群优化算法来找到使模拟结果与每种湿度条件下记录的试验最佳匹配的参数值。结果表明,随着手指水分含量增加,主体组织的柔软度降低。湿润手指模型的表皮最柔软,而自然手指模型的粘度最高。

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