Tymms Chelsea, Zorin Denis, Gardner Esther P
Department of Computer Science, New York University , New York, New York.
Department of Neuroscience and Physiology and NYU Neuroscience Institute, New York University School of Medicine , New York, New York.
J Neurophysiol. 2018 Mar 1;119(3):862-876. doi: 10.1152/jn.00564.2017. Epub 2017 Nov 22.
Surface roughness is one of the most important qualities in haptic perception. Roughness is a major identifier for judgments of material composition, comfort, and friction and is tied closely to manual dexterity. Some attention has been given to the study of roughness perception in the past, but it has typically focused on noncontrollable natural materials or on a narrow range of artificial materials. The advent of high-resolution three-dimensional (3D) printing technology provides the ability to fabricate arbitrary 3D textures with precise surface geometry to be used in tactile studies. We used parametric modeling and 3D printing to manufacture a set of textured plates with defined element spacing, shape, and arrangement. Using active touch and two-alternative forced-choice protocols, we investigated the contributions of these surface parameters to roughness perception in human subjects. Results indicate that large spatial periods produce higher estimations of roughness (with Weber fraction = 0.19), small texture elements are perceived as rougher than large texture elements of the same wavelength, perceptual differences exist between textures with the same spacing but different arrangements, and roughness equivalencies exist between textures differing along different parameters. We posit that papillary ridges serve as tactile processing units, and neural ensembles encode the spatial profiles of the texture contact area to produce roughness estimates. The stimuli and the manufacturing process may be used in further studies of tactile roughness perception and in related neurophysiological applications. NEW & NOTEWORTHY Surface roughness is an integral quality of texture perception. We manufactured textures using high-resolution 3D printing, which allows precise specification of the surface spatial topography. In human psychophysical experiments we investigated the contributions of specific surface parameters to roughness perception. We found that textures with large spatial periods, small texture elements, and irregular, isotropic arrangements elicit the highest estimations of roughness. We propose that roughness correlates inversely with the total contacted surface area.
表面粗糙度是触觉感知中最重要的特性之一。粗糙度是判断材料成分、舒适度和摩擦力的主要指标,并且与手部灵巧性密切相关。过去对粗糙度感知的研究有所关注,但通常集中在不可控的天然材料或范围狭窄的人造材料上。高分辨率三维(3D)打印技术的出现,使得制造具有精确表面几何形状的任意3D纹理成为可能,可用于触觉研究。我们使用参数化建模和3D打印制造了一组具有确定元素间距、形状和排列的纹理板。通过主动触摸和二选一强迫选择协议,我们研究了这些表面参数对人类受试者粗糙度感知的影响。结果表明,较大的空间周期会产生更高的粗糙度估计值(韦伯分数=0.19),较小的纹理元素比相同波长的大纹理元素被感知为更粗糙,具有相同间距但不同排列的纹理之间存在感知差异,并且沿不同参数变化的纹理之间存在粗糙度等效性。我们认为乳头嵴充当触觉处理单元,神经集合对纹理接触区域的空间轮廓进行编码以产生粗糙度估计。这些刺激和制造过程可用于进一步研究触觉粗糙度感知及相关神经生理学应用。新内容与值得关注之处 表面粗糙度是纹理感知的一个不可或缺的特性。我们使用高分辨率3D打印制造纹理,这使得能够精确指定表面空间地形。在人体心理物理学实验中,我们研究了特定表面参数对粗糙度感知的影响。我们发现,具有大空间周期、小纹理元素以及不规则、各向同性排列的纹理会引发最高的粗糙度估计值。我们提出粗糙度与总接触表面积成反比。