Anthropomorphic Classification of Tactile Qualities of Woven Fabrics Based on Skin/Textile Friction-Induced Vibrations
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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.Keywords:
Textile
Tactile sensor
Tactile display
Sensation
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Tactile sensation for four nylon6 satin fabrics of different fiber fineness has been examined. Four grades of fineness of the fibers were employed as 0.74 (micro-fiber), 1.4, 4.4, and 56 dtex. Several tactile adjectives effective to express tactile sensation were selected by means of factor analysis for questionnaire data. The tactile adjectives selected were related to feeling and sense to heat and moisture. The evaluation data for tactile sensation of fabrics were analyzed by paired comparison method using the selected adjectives. It is stressed that the correspondence of tactile sensation to physical properties of the fabrics was observed for fiber fineness of about ldtex or more. It has been further clarified tin the present work that the micro fiber fabric shows a specific tactile sensation compared with normal fiber fabric.
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Fiber type
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A tactile rendering system for fabric textures is presented to improve the tactile sensations in humancomputer interactions in this paper. A tactile platform based on electrovibration is constructed to produce the virtual tactile sensation. The voltage amplitude perception threshold and differential threshold of human beings on the system are measured by a series of experiments. On this basis, the relationship between the stimulus signal and tactile perception is established using psychophysical experiments. A texture library of fabrics is then created by using a surface morphology analyzer. The amplitude of the corresponding voltage for rendering textures can be calculated according to the established relationship between the stimulus signal and tactile perception. As a new fabric texture image is input to the system, convolutional neural network (CNN) is used to match the texture with the texture library and then the corresponding stimulus signal can be generated. The above system is finally evaluated and numerically quantified through experiments.
Stimulus (psychology)
Tactile Perception
Tactile sensor
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Tactile Perception
Tactile sensor
Tribometer
Characterization
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The tactile properties of fabrics are the most important features that affect the quality of the finished products and the decision of the customer when purchasing one. Conventional methods for evaluating the comfort and the impact of the fabric on human senses are based on subjective examination of tactile properties. Among the various properties of fabrics, surface features are those that might contribute most to the individual perception when touching the fabric. The texture of the fabric can be evaluated by sensation of touch (tactile evaluation), sensation of sight (visual evaluation), and on the basis of the two senses combined together (tactile-visual evaluation). One of the goals of this paper is to identify the most appropriate attributes for description of fabrics, and also to indicate some of the contemporary research on prediction of tactile properties of fabrics.
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Weave, yarn density, yarn count, fiber material and so on of woven fabrics greatly affect their surface characteristics. Surface characteristics of a fabric are important factor for consumers and textile producers in order to evaluate its fabric hand. However, there is no simple system to easily measure its surface characteristics. This study uses a simple tactile sensor that can measure the friction coefficients of fabric surfaces and tries to evaluate their surface characteristics from obtained values. We traced surfaces of plural fabrics that differ in yarn, weave and yarn density with the tactile sensor, and measured variation of the friction coefficients with respect to the trace distance. This study introduces some evaluation values from the measured variation of the friction coefficients and compares them with results by KES, which is the ordinary system to evaluate surface characteristics of a fabric. As a result, the study confirmed that proposed method easily evaluates the geometrical and frictional properties of woven fabrics as their fabric hand, and also can estimate the yarn density of woven fabric by analyzing the oscillation period of variation of friction coefficient.
Textile
Woven fabric
Tactile sensor
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Tactile Perception of Roughness and Hardness to Discriminate Materials by Friction-Induced Vibration
The human fingertip is an exquisitely powerful bio-tactile sensor in perceiving different materials based on various highly-sensitive mechanoreceptors distributed all over the skin. The tactile perception of surface roughness and material hardness can be estimated by skin vibrations generated during a fingertip stroking of a surface instead of being maintained in a static position. Moreover, reciprocating sliding with increasing velocities and pressures are two common behaviors in humans to discriminate different materials, but the question remains as to what the correlation of the sliding velocity and normal load on the tactile perceptions of surface roughness and hardness is for material discrimination. In order to investigate this correlation, a finger-inspired crossed-I beam structure tactile tester has been designed to mimic the anthropic tactile discrimination behaviors. A novel method of characterizing the fast Fourier transform integral (FFT) slope of the vibration acceleration signal generated from fingertip rubbing on surfaces at increasing sliding velocity and normal load, respectively, are defined as kv and kw, and is proposed to discriminate the surface roughness and hardness of different materials. Over eight types of materials were tested, and they proved the capability and advantages of this high tactile-discriminating method. Our study may find applications in investigating humanoid robot perceptual abilities.
Tactile Perception
Rubbing
Tactile sensor
Reciprocating motion
Tactile display
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Texture (cosmology)
Textile
Envelope (radar)
Tribometer
Feature (linguistics)
SIGNAL (programming language)
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Textile
Tactile sensor
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Tactile Perception
Tactile sensor
Middle finger
Texture (cosmology)
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