Tactile Textures Research Articles

Processing the fine-grained features of tactile textures involves the primary somatosensory cortex

Abstract Dynamic tactile perception and discrimination of textures require the ability to encode and differentiate complex vibration patterns elicited at the level of the skin when sliding against a surface. Whether the primary somatosensory cortex (S1) can encode the fine-grained spectrotemporal features distinguishing textures remains debated. To address this question, EEG frequency-tagging was used to characterize responses to vibrotactile oddball contrasts between two textures. In a first session designed to identify the topographical distribution of responses originating from the hand and foot representations in S1, standard and deviant stimuli were pure sinusoidal vibrations differing in frequency and intensity. In a second session, standard and deviant stimuli were two different snippets of bandpass-filtered white noise matched in terms of intensity and average frequency content, but differing in terms of their complex spectrotemporal content. Using the S1 functional localizer, we showed that oddball responses to a spectrotemporal contrast follow the somatotopical organization of S1. Our results suggest that the encoding of fine-grained spectrotemporal features associated with different vibration patterns involves S1.

A melody that sings itself

In his lectures on the philosophy of nature, Maurice Merleau-Ponty interprets Jakob von Uexküll’s notion of Umwelt as akin to a melody. This essay outlines von Uexküll’s perspective on the feasibility of translating non-acoustic elements (optical: colours, shapes, and figures; haptic: tactile textures, flavours, tastes, and scents) into sounds or musical notes to compose a melody. It poses several inquiries: Does the link between melody and nature render natural entities as musical notes? Do the components of an entity constitute anatomical notes in the melody that defines the entity itself? Is it conceivable to distil every moment in life into a “note” symbol on a musical scale, characterised by specific duration, pitch, and volume? Melody, rhythm, and harmony are considered sophisticated “structures” that articulate and convey the essence of nature’s existence. Moreover, every human, every living creature, be it animal or plant, possesses a subjective “biological” interiority. The inner realm of each living subject, along with the objects in the external world, are enveloped within an atmosphere—a musical Umwelt. Humans exist within this musical milieu or atmosphere.

Crossmodal associations between naturally occurring tactile and sound textures.

This study investigates the crossmodal associations between naturally occurring sound textures and tactile textures. Previous research has demonstrated the association between low-level sensory features of sound and touch, as well as higher-level, cognitively mediated associations involving language, emotions, and metaphors. However, stimuli like textures, which are found in both modalities have received less attention. In this study, we conducted two experiments: a free association task and a two alternate forced choice task using everyday tactile textures and sound textures selected from natural sound categories. The results revealed consistent crossmodal associations reported by participants between the textures of the two modalities. They tended to associate more sound textures (e.g., wood shavings and sandpaper) with tactile surfaces that were rated as harder, rougher, and intermediate on the sticky-slippery scale. While some participants based the auditory-tactile association on sensory features, others made the associations based on semantic relationships, co-occurrence in nature, and emotional mediation. Interestingly, the statistical features of the sound textures (mean, variance, kurtosis, power, autocorrelation, and correlation) did not show significant correlations with the crossmodal associations, indicating a higher-level association. This study provides insights into auditory-tactile associations by highlighting the role of sensory and emotional (or cognitive) factors in prompting these associations.

FASHION VISION BEYOND THE EYES: HOW FASHION BECOMES INCLUSIVE FOR PEOPLE WITH VISUAL IMPAIRMENTS

The present study addresses inclusive fashion as a strategy to promote social inclusion and stimulate the cognitive and emotional development of individuals with visual impairments. The research aimed to create an approach that would utilize sensory elements in fashion pieces, allowing individuals who were born blind or lost their vision early in life to create tactile representations of shapes around them. The methodology is characterized as applied in nature, involving active collaboration between participants with visual impairments and professionals in the fashion industry. Customized pieces were developed, considering the individual preferences and specific needs of each participant. The qualitative approach included interviews with three visually impaired individuals and observations to comprehend the experiences, perceptions, and challenges faced by these individuals in the context of fashion. The results indicate that the inclusion of tactile textures and functional elements, such as larger zippers and snap buttons, contributes to a more autonomous and enriching experience in the selection and use of clothing. Additionally, technology plays a significant role, with wearable devices and applications assisting in color identification and reading digital Braille labels. The proposed approach not only enhances the tactile perception of clothing but also promotes individual expression and autonomy among people with visual impairments. By creating mental representations of shapes around them, inclusive fashion stimulates cognitive and creative development in these individuals. It can be concluded that this approach represents a significant step towards a more inclusive society, where fashion is accessible to everyone, regardless of their visual abilities.

Evidence for vibration coding of sliding tactile textures in auditory cortex

Evidence for vibration coding of sliding tactile textures in auditory cortex

Pattern characterization using topological data analysis: Application to piezo vibration striking treatment

Quantifying patterns in visual or tactile textures provides important information about the process or phenomena that generated these patterns. In manufacturing, these patterns can be intentionally introduced as a design feature, or they can be a byproduct of a specific process. Since surface texture has significant impact on the mechanical properties and the longevity of the workpiece, it is important to develop tools for quantifying surface patterns and, when applicable, comparing them to their nominal counterparts. While existing tools may be able to indicate the existence of a pattern, they typically do not provide more information about the pattern structure, or how much it deviates from a nominal pattern. Further, prior works do not provide automatic or algorithmic approaches for quantifying other pattern characteristics such as depths’ consistency, and variations in the pattern motifs at different level sets. This paper leverages persistent homology from Topological Data Analysis (TDA) to derive noise-robust scores for quantifying motifs’ depth and roundness in a pattern. Specifically, sublevel persistence is used to derive scores that quantify the consistency of indentation depths at any level set in Piezo Vibration Striking Treatment (PVST) surfaces. Moreover, we combine sublevel persistence with the distance transform to quantify the consistency of the indentation radii, and to compare them with the nominal ones. Although the tool in our PVST experiments had a semi-spherical profile, we present a generalization of our approach to tools/motifs of arbitrary shapes thus making our method applicable to other pattern-generating manufacturing processes.

Identification of Properties and Morphological Characteristics in Tactile Textures: a Study on Educational Graphics and Cartographies for Visual Impaired Children

RESUMO: Este artigo explora as texturas táteis que têm sido utilizadas na confecção de mapas e imagens temáticas para crianças com deficiência visual no Chile nos últimos 20 anos. De um grupo representativo composto por mais de 300 lâminas de conteúdo educacional inclusivo, foram selecionadas 14 texturas para identificar sua natureza, propriedades psicofísicas e características morfológicas a partir de sua composição geométrica. O objetivo foi gerar as bases teóricas e tecnológicas relacionadas ao design e à produção digital de mapas, imagens e gráficos táteis. O trabalho buscou tipificar as formas de relevo e suas possíveis aplicações pelo uso de padrões de repetição que permitam melhorar a linguagem e o reconhecimento das texturas envolvidas com o intuito de expandir e diversificar seu uso em material educativo inclusivo no ensino e na disseminação do conhecimento por meio do toque.

Handy-Type Tactile Sensor for Object Recognition Using Convolutional Neural Networks

Tactile sensation obtained from touch is one of the most important factors that determine the impression of an object. A method for identifying tactile textures is required because individual differences exist in feeling of tactile textures. In this study, we propose a handy-type tactile sensor for object recognition using convolutional neural networks (CNNs). The sensor consists of a three-axis pressure sensor and an optical motion sensor for a mouse and can detect time-series data. The object is identified using CNN from the time-series data, namely, pressure and speed of the sensor, when the sensor is moved by a user using a hand. Thus, the sensor system configuration is simple without needing a drive device, and it can be possibly constructed at a low cost. Fifteen types of objects were identified using the prototype sensor. The total average correct recognition rate by one specific user in this study was 77%. Further, the total average recognition rate by four separate users without considering each individual use of the sensor system was 48%. Although the problem in individual identification remained, this result demonstrated the potential for identification application. The proposed sensor system can be used as a functional and useful device.

Feeling Illusory Textures Through a Hole: Rotating Frame At Skin-Object Interface Modifies Perceived Tactile Texture.

Modulating tactile texture perception for the surface of real objects is a promising way to artificially present various tactile textures. Here, we propose a simple method of modulating tactile textures for various materials, which is named the rotating-frame method. In the method, one touches an arbitrary material's surface through a hole in a cardboard frame. When the frame is rotated between the hand and material, the tactile texture of the material is perceived as if it has turned into another material. We investigated the qualitative and quantitative characteristics of the illusory modulation created by the method in a series of psychophysical experiments. We found that the method altered the tactile textures of the surfaces of touched materials such as glass and carpet to seem softer, smoother, slipperier, and warmer than they actually are. The illusory texture change occurred robustly when the method was applied with different categories of materials. Our method paves the way for the development of simple techniques for texture augmentation that can be applied to a wide range of materials and do not disrupt stable direct contact between the hand and the materials.

Understanding the Effects of Tactile Grating Patterns on Perceived Roughness Over Ultrasonic Friction Modulation Surfaces.

Our study aims to investigate the effects of grating patterns of perceived roughness on surfaces with ultrasonic friction modulation, and also to examine user performance of identifying different numbers of grating patterns. In designing grating-based tactile textures, the widths of low- and high-friction zones are a crucial factor for generating grating patterns that convey roughness sensation. However, few studies have explored the design space of efficient grating patterns that users can easily distinguish and identify via roughness perception. Two experiments were carried out. In the first experiment, we conducted a magnitude estimation of perceived roughness for both low- and high-friction zones, each with widths of 0.13, 0.25, 0.38, 0.5, 1.0, 1.5, 2.0, 3.5, and 5.5mm. In the second experiment, we required participants to identify 5 pattern groups with 2-6 patterns respectively. Perceived roughness fitted a linear trend for low- or high-friction zones with widths of 0.38mm or lower. Perceived roughness followed an inverted U-shaped curve for low- or high-friction zones with widths greater than 0.5mm but less than 2.0mm. The peak points occurred at the widths of 0.38mm for both low- and high-friction zones. The statistical analysis indicates that both low- and high-friction zones had similar effects on human perception of surface roughness. In addition, participants could memorize and identify up to four tactile patterns with identification accuracy rates higher than 90% and average reaction time less than 2.2 s. The relation between perceived roughness and varying widths of grating patterns follows linear or inverted U-shape trends. Participants could efficiently identify 4 or fewer patterns with high accuracy (>90%) and short reaction time (<2.2 s). Our findings can contribute to tactile interface design such as tactile alphabets and target-approaching indicators.

Tactile Texture Rendering for Electrostatic Friction Displays: Incorporation of Low-Frequency Friction Model and High-Frequency Textural Model.

Tactile texture presentation on touch panels enhances their usability and realizes immersive user interfaces. This study develops a tactile texture rendering method for electrostatic friction displays. The method combines two rendering models for material textures compared with previous studies which focused on either of these two models. One of these models is a physical model that simulates low-frequency frictional signals depending on the exploratory finger velocities and contact loads. The other is an autoregression-based data-driven model for high-frequency textural friction. For user studies, we compared combining the two models with using only the physical model for the four types of materials. Although the effectiveness varied across the materials, the subjectively judged realism and identification of the materials were improved for the combined condition. The new method combining high-frequency textural information and low-frequency physical model-based friction is expected to provide realistic tactile textures for electrostatic surface tactile displays.

Effects of Tactile Textures on Preference in Visuo-Tactile Exploration

The use of haptic technologies has recently become immensely essential in Human-Computer Interaction to improve user experience and performance. With the introduction of tactile feedback on a touchscreen device, commonly known as surface haptics, several applications and interaction paradigms have become a reality. However, the effects of tactile feedback on the preference of 2D images in visuo-tactile exploration task on touchscreen devices remain largely unknown. In this study, we investigated differences of preference score (the tendency of participants to like/dislike a 2D image based on its visual and tactile properties), reach time, interaction time, and response time under four conditions of feedback: no tactile feedback, high-quality of tactile information (sharp tactile texture), low-quality of tactile information (blurred tactile texture), and incorrect tactile information (mismatch tactile texture). The tactile feedback is rendered in the form of roughness that is simulated by modulating the friction between the finger and the surface and is derived from the 2D image. Thirty-six participants completed visuo-tactile exploration tasks for a total of 36 trials (3 2D images × 4 tactile textures × 3 repetitions). Results showed that the presence of tactile feedback enhanced users’ preference (tactile feedback conditions were rated significantly higher than the no tactile feedback condition for preference regardless of the quality/correctness of tactile feedback). This finding is also supported through results from self-reporting where 88.89% of participants preferred to experience the 2D image with tactile feedback. Additionally, the presence of tactile feedback resulted in significantly larger interaction time and response time compared to the no tactile feedback condition. Furthermore, the quality and correctness of tactile information significantly impacted the preference rating (sharp tactile textures were rated statistically higher than blurred tactile and mismatched tactile textures). All of these findings demonstrate that tactile feedback plays a crucial role in users’ preference and thus motivates further the development of surface haptic technologies.

Effect of Physical Challenging Activity on Tactile Texture Recognition for Mobile Surface

Previous research demonstrated the ability for users to accurately recognize tactile textures on mobile surface. However, the experiments were only run in a lab setting and the ability for users to recognize tactile texture in a real-world environment remains unclear. In this paper, we investigate the effects of physical challenging activities on tactile textures recognition. We consider five conditions: (1) seated on an office, (2) standing in an office, (3) seated in the tramway, (4) standing in the tramway and (5) walking in the street. Our findings indicate that when walking, performances deteriorated compared to the remainder conditions. However, despite this deterioration, the recognition rate stay higher than 82% suggesting that tactile texture could be effectively recognized and used by users in different physical challenges activities including walking.

End-to-End Tactile Feedback Loop: From Soft Sensor Skin Over Deep GRU-Autoencoders to Tactile Stimulation

Tactile feedback is a key sensory channel that contributes to our ability to perform precise manipulations. In this regard, sensor skin provides robots with the sense of touch making them increasingly capable of dexterous object manipulation. However, in applications like teleoperation, the complex sensory input of an infinite number of different textures must be projected to the human user's skin in a meaningful manner. In addressing this issue, a deep gated recurrent unit-based autoencoder (GRU-AE) that captured the perceptual dimensions of tactile textures in latent space was deployed to implicitly understand unseen textures. The expression of unknown textures in this latent space allowed for the definition of a control law to effectively drive tactile displays and to convey tactile feedback in a psycho-physically meaningful manner. The approach was experimentally verified by evaluating the prediction performance of the GRU-AE on seen and unseen data that were gathered during active tactile exploration of objects commonly encountered in daily living. A user study on a custom-made tactile display was conducted in which real tactile perceptions in response to active tactile object exploration were compared to the emulated tactile feedback using the proposed tactile feedback loop. The results suggest that the deep GRU-AE for tactile display control offers an effective and intuitive method for efficient end-to-end tactile feedback during active tactile texture exploration.

Tactile Roughness Perception of Virtual Gratings by Electrovibration.

Realistic display of tactile textures on touch screens is a big step forward for haptic technology to reach a wide range of consumers utilizing electronic devices on a daily basis. Since the texture topography cannot be rendered explicitly by electrovibration on touch screens, it is important to understand how we perceive the virtual textures displayed by friction modulation via electrovibration. We investigated the roughness perception of real gratings made of plexiglass and virtual gratings displayed by electrovibration through a touch screen for comparison. In particular, we conducted two psychophysical experiments with ten participants to investigate the effect of spatial period and the normal force applied by finger on roughness perception of real and virtual gratings in macro size. We also recorded the contact forces acting on the participants' finger during the experiments. The results showed that the roughness perception of real and virtual gratings are different. We argue that this difference can be explained by the amount of fingerpad penetration into the gratings. For real gratings, penetration increased tangential forces acting on the finger, whereas for virtual ones where skin penetration is absent, tangential forces decreased with spatial period. Supporting our claim, we also found that increasing normal force increases the perceived roughness of real gratings while it causes an opposite effect for the virtual gratings. These results are consistent with the tangential force profiles recorded for both real and virtual gratings. In particular, the rate of change in tangential force ( dFt/dt) as a function of spatial period and normal force followed trends similar to those obtained for the roughness estimates of real and virtual gratings, suggesting that it is a better indicator of the perceived roughness than the tangential force magnitude.

Using a convolutional neural network to construct a pen-type tactile sensor system for roughness recognition

The tactile texture of a product is one of many important factors that influences an impression of a product. Numerical evaluation methods for recognizing tactile texture measures, such as roughness, are required because there are indeed individual differences in how users experience tactile textures. In this paper, we propose a tactile sensor to recognize roughness using a convolutional neural network (CNN). Our sensor system consists of a pressure sensor and a six-axis acceleration sensor for detecting time-series data. The sensor measures time-series data, which are the pressure, speed, and posture of the sensor when the sensor is touching an object and is moved by a user. The surface roughness is calculated from these time-series data using a CNN. Here, our system configuration is simple and therefore easy and inexpensive to construct. To evaluate our approach, we constructed a prototype sensor and measured the roughness of six objects. The average correct recognition rate proved to be 71% for the experimental data acquired by one user, which are categorized into learning data and evaluation data. Further, the total average recognition rate for evaluation data by our five users for considering each individual using the sensor system was 42%. While the problem of roughness recognition by each individual user remains, we were able to show the possibility of roughness recognition via our approach. We conclude that our proposed sensor system is useful as a functional and useful device.

The effect of white and black surface for tactile textures : an experiment on elderly persons

The effect of white and black surface for tactile textures : an experiment on elderly persons

Emotional visual stimuli affect the evaluation of tactile stimuli presented on the arms but not the related electrodermal responses

Considering the wealth of recent studies on affective touch, to date, little research addressed the role of the other sensory modalities in the modulation of hedonic tactile perception. Here, we investigated the behavioral and electrodermal signature of the interaction between simultaneously presented visual and tactile stimuli. In three experiments, participants were presented with emotional pictures (international affective picture system; IAPS), while their forearm was gently stroked by means of different tactile textures (i.e., sandpaper, satin, tinfoil, abrasive sponge, and skin-to-skin contact). In Experiment 1, the participants evaluated the pleasantness of the tactile stimulation received, while in Experiment 2 they evaluated the pictures emotional valence. In Experiment 3 the participants rated the pleasantness, the smoothness and the softness of the textures; skin conductance responses (SCRs) were also measured. In sum, the results revealed that while the visual valence ratings were not modulated by the tactile stimulation, the hedonic and sensory tactile ratings were modulated by the visual presentation of both positively and negatively valenced pictures, as well as by neutral pictures. The modulatory effects occurring during visuo-tactile interactions might thus be not necessarily reciprocal. Moreover, the SCRs were not differently affected by the visuo-tactile or tactile conditions of stimulus presentation, suggesting a dissociation between behavioral and electrodermal effects in multisensory interactions.

Modeling Semantically Multilayered Affective and Psychophysical Responses Toward Tactile Textures

Subjective responses related to touch are described via perceptual and affective adjectives. Understanding relationships among such responses is useful for industrial surface design. We developed a method for investigating relationships among touch-related responses by constructing multilayered adjective models without assumptions regarding model structure such as adjective hierarchy or a definition of layers. The method consists of two processes through which a model structure and parameters are estimated. To acquire the model structure, subjectively evaluated causal relationships among adjective pairs are used. Free parameters, such as effects among adjectives, are then statistically estimated through sensory evaluation and structural equation modeling. To validate the method, two models with different levels of details were developed using 29 adjective pairs and 46 texture samples. For example, the model with three layers, which we categorized into psychophysical, affective, and hedonic layers, was constructed. Moreover, a detailed model with four layers was provided, which was more complex than previously reported models. The present method helps advance our understanding and design of connections among subjective surface ratings.

Perceptual Constancy in the Reproduction of Virtual Tactile Textures With Surface Displays

For very rough surfaces, friction-induced vibrations contain frequencies that change in proportion to sliding speed. Given the poor capacity of the somatosensory system to discriminate frequencies, this fact raises the question of how accurately finger sliding speed must be known during the reproduction of virtual textures with a surface tactile display. During active touch, ten observers were asked to discriminate texture recordings corresponding to different speeds. The samples were constructed from a common texture, which was resampled at various frequencies to give a set of stimuli of different swiping speeds. In trials, they swiped their finger in rapid succession over a glass plate, which vibrated to accurately reproduce three texture recordings. Two of these recordings were identical and a third differed in that the sample represented a texture swiped at a speed different from the other two. Observers identified which of the three samples felt different. For a metal mesh texture recording, seven observers reported differences when the speed varied by 60, 80, and 100mm/s while the other three did not reach a discrimination threshold. For a finer leather chamois texture recording, thresholds were never reached in the 100mm/s range. These results show that the need for high-accuracy measurement of swiping speed during texture reproduction may actually be quite limited compared to what is commonly found in the literature.