Influence of Surface Topography on the Tactile Friction of Medical Compression Textiles against a Mechanical Skin Model

Influence of surface topography on the tactile friction of medical compression textiles was studied in this paper. The friction behavior was investigated for three kinds of medical textiles with various structures and compositions by using a textile friction analyzer under dry condition. In order to simulate the contacts of textiles/human finger, a mechanical skin model with similar texture to the skin and applied normal load oflN were selected. Meanwhile, the 3D surface topography of textiles was measured using a digital microscope. The topographical data were analyzed concerning height distribution and material ratio, and the real contact area was estimated as a function of penetration depth. Results showed that the investigated textiles revealed a significant variation on the friction coefficients, which were （ 0.41 ± 0.01 ） （ polyamide, jersey 2 × 2 ）, （0.56 ± 0. 01） （cotton, jersey 2×2） and （0. 47 ± 0. 01） （polyamide, jersey 1 × 1 ）, respectively. The textile with higher friction coefficient was found to own a relative compact and homogenous surface and larger contact area, vice versa.     

Psychometric Properties of Geometrical Texture Features for Tactile Roughness Sensation of Fabric Surfaces

The lack of understanding of the psychometric properties on the basic texture features forming tactile texture sense hinders the development of haptic rendering technology of textiles. The differential threshold and Weber fraction were investigated for a deep understanding of how surface texture features of fabrics affect the perceived roughness sensation by the constant stimulus method and the paired comparison method. The results showed that the differential threshold for the mean deviation of surface profile was0. 86 μm,and that the differential threshold of texture spatial period(TSP) was 2. 48 mm. And also,the difference thresholds and Weber fraction were affected by the reference stimulus intensity. As there is a significant interaction between four extracted texture feature indexes,any of the indexes alone cannot represent roughness sensation of fabrics.     

Dependence of Softness on Fabric Surface Quality and Compressibility

The term ＂softness＂ is loosely used to describe the physical as well as sensory attributes of fabric and other textiles, and several psychophysicai evaluation methods as well as its predicting equations exist. However, the information for physiological mechanism of fabric softness is lack. To explain the blomechauical and the potential neurophysiologicai phecnomenon for exploring fabric softness, accompanying to the procedures in manual exploration for softness and the anatomical multllayor structures of human finer, a contact finite dement （FE） model between finger and fabric is made to conduct an active contact analysis. In present FE model, the effect of surface friction index, compression modulus, Poisson＇s ratio of fabric on softness dlscrimination is Investigated. The interests are in the contributlons of these fabric property variables to contact area, Interracial friction shear stress and contact pressure distributions, which arc significant cognitive variables or stimulus parameters in peripheral neural levels. The mechanistic data for fabric specimens indicates that the basis for the perception of softness of flexible and bulk fabric is likely on the spatial variation of pressure on the skin （or, equivalently the skin displacement and its derivatives） resulting from surface friction phenomenon and compression property of fabric. In present model, however, the effect of Poisson＇s ratio on the total force exerted by fingertip is not significant statistically. Therefore, compression modulus of fabric is, not the only underlying physical variable accounting for peripheral neural response, and also the surface friction phenomenon plays an important role in feeltouch softness of fabric, i.e. the compressibility and surface properties of fabric arc the necessary physical variables involved for the haptic rendering of its softness.     

织物手感的认知原理及其研究

织物手感是纺织品十分重要的性能之一．经过近一个世纪的研究，随着科学技术的发展，对织物手感的表征和评价取得了不少成果．但由于人们对大脑认知行为的认识尚不成熟，对织物手感的神经认知原理还处于探索阶段，导致对织物手感形成机制的理解不深入，从而限制了该方面研究的进展．通过分析织物手感形成的生理基础，归纳了探索织物手感方面的研究工作，试图从认知心理学角度澄清以往在该领域研究工作的模糊认识，分析传统上从认知心理学角度研究织物手感认知属性空间的不足．同时，结合认知神经科学最新的研究结果，寻求织物手感定量表征的发展方向．     

Anthropomorphic Classification of Tactile Qualities of Woven Fabrics Based on Skin/Textile Friction-Induced Vibrations

The common method classifying tactile qualities of fabrics is indirectly based on their difference of purely mechanical and physical properties. When human skin slides across fabric surfaces, the friction interaction between fabrics and skin will occur and trigger the cutaneouS tactile receptors, which are responsible for perceived tactile sensation. By the extracted features from friction- induced vibration signals, this paper presents an anthropomorphic classification method classifying tactile qualities of fabrics. The friction-induced vibration signals are recorded by a three-axis accelerator sensor, and the entice testing procedure is conducted in an anthropomorphic way to obtain vibration signals. The fast Fourier transform （FFT） is applied to analyzing the recoded signals, and then the classification features are extracted from the FFT data by the neurophysiological properties of tactile receptors. The extracted features are used to classify fabric samples by the softness sensation and the roughness sensation, respectively, and the classification performance is checked by a comparison with those in a sensory evaluation procedure. The results showed that the anthropomorphic objective classification method was precise and efficient to clarify tactile qualities of woven fabrics.     

基于一种自适应突触学习的动态相关系数与相位同步分析

本文提出了一种自适应的突触学习模型模拟了神经突触的可塑性,通过这种学习规则在定义的动态相关系数指标下发现,可以使得一般非全同随机神经网络达到同步,表明该方法具有较好的鲁棒性.为了刻画网络在整体上的相同步提出了基于Poincare截面的相位定义法,将动作电位峰值所在的位置定义为Poincare截面,进而定义同步差,网络相位同步.网络相位差计算结果显示,任意两个神经元之间的相位差随着时间变化趋于常数,即网络中任意两个神经元出现相同步,神经网络平均相位差趋于常数,神经网络出现全局的相位同步.