A Quantitative Perceptual Model for Tactile Roughness
A Quantitative Perceptual Model for Tactile Roughness
复制标题
触觉粗糙度的定量感知模型
DOI：
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复制
发表时间：
2018
影响因子：
6.2
通讯作者：
D. Zorin
中科院分区：
文献类型：
--
作者：
Chelsea Tymms;E. P. Gardner;D. Zorin
每个人都用触觉来探索世界，粗糙度是触觉感知中最重要的品质之一。粗糙度是判断材料成分、舒适度和摩擦力的主要标识符，并且与手动灵活性密切相关。高分辨率3D打印技术的出现提供了制造具有赋予触觉特性的表面几何形状的任意3D纹理的能力。在这项工作中，我们解决的问题，映射对象的几何形状，触觉粗糙度。我们制造了一组精心设计的刺激，并使用它们在实验中与人类受试者建立一个感知空间的粗糙度。然后，我们将这个空间与从接触纹理几何形状的人类皮肤的弹性模拟中获得的应变场获得的定量模型相匹配，该模型来自神经科学和心理物理学的过去研究。我们演示了如何将此模型应用于预测和改变表面粗糙度，我们展示了几个应用程序的背景下制造。
Everyone uses the sense of touch to explore the world, and roughness is one of the most important qualities in tactile perception. Roughness is a major identifier for judgments of material composition, comfort, and friction, and it is tied closely to manual dexterity. The advent of high-resolution 3D printing technology provides the ability to fabricate arbitrary 3D textures with surface geometry that confers haptic properties. In this work, we address the problem of mapping object geometry to tactile roughness. We fabricate a set of carefully designed stimuli and use them in experiments with human subjects to build a perceptual space for roughness. We then match this space to a quantitative model obtained from strain fields derived from elasticity simulations of the human skin contacting the texture geometry, drawing from past research in neuroscience and psychophysics. We demonstrate how this model can be applied to predict and alter surface roughness, and we show several applications in the context of fabrication.
DOI：
10.1115/1.1613673
发表时间：
2003-10-01
影响因子：
1.7
作者：
Dandekar, K;Raju, BI;Srinivasan, MA
通讯作者：
Srinivasan, MA
影响因子：
11.2
作者：
Elkharraz, Galal;Thumfart, Stefan;Henson, Brian
通讯作者：
Henson, Brian