Making Tactile Textures with Predefined Affective Properties

A process for the design and manufacture of 3D tactile textures with predefined affective properties was developed. Twenty four tactile textures were manufactured. Texture measures from the domain of machine vision were used to characterize the digital representations of the tactile textures. To obtain affective ratings, the textures were touched, unseen, by 107 participants who scored them against natural, warm, elegant, rough, simple, and like, on a semantic differential scale. The texture measures were correlated with the participants' affective ratings using a novel feature subset evaluation method and a partial least squares genetic algorithm. Six measures were identified that are significantly correlated with human responses and are unlikely to have occurred by chance. Regression equations were used to select 48 new tactile textures that had been synthesized using mixing algorithms and which were likely to score highly against the six adjectives when touched by participants. The new textures were manufactured and rated by participants. It was found that the regression equations gave excellent predictive ability. The principal contribution of the work is the demonstration of a process, using machine vision methods and rapid prototyping, which can be used to make new tactile textures with predefined affective properties

Human Roughness Perception and Possible Factors Effecting Roughness Sensation

Surface texture sensation is significant for business success, in particular for solid surfaces for most of the materials; including foods, furniture or fabrics. Applications of roughness perception are still unknown, especially under different conditions such as lubricants with varying viscosities, different temperatures, or under different force loads during the observation of the surface. This work aims to determine the effect of those unknown factors, with applied sensory tests on 62 healthy participants. Roughness sensation of fingertip was tested under different lubricants including water and diluted syrup solutions at room temperature (25oC) and body temperature (37oC) by using simple pairwise comparison in order to observe the just noticeable difference threshold and perception levels. Additionally in this research applied force load during roughness observation was tested with pair-wise ranking method to illustrate its possible effect on the human sensation. Obtained results showed that human roughness discrimination capability reduces with an increasing viscosity of the lubricant, where the temperature was not found to be significant. Moreover, the increase in the applied force load showed an increase in the sensitivity of roughness discrimination capability. Observed effects of the applied factors were also used for estimating the oral sensation of texture during eating. These findings are significant for our fundamental understanding to the texture perception, but also could find applications in the material sciences which may include food sciences that needs information about texture perception for the development of new foods with controlled textural features

Touching on elements for a non-invasive sensory feedback system for use in a prosthetic hand

Hand amputation results in the loss of motor and sensory functions, impacting activities of daily life and quality of life. Commercially available prosthetic hands restore the motor function but lack sensory feedback, which is crucial to receive information about the prosthesis state in real-time when interacting with the external environment. As a supplement to the missing sensory feedback, the amputee needs to rely on visual and audio cues to operate the prosthetic hand, which can be mentally demanding. This thesis revolves around finding potential solutions to contribute to an intuitive non-invasive sensory feedback system that could be cognitively less burdensome and enhance the sense of embodiment (the feeling that an artificial limb belongs to one’s own body), increasing acceptance of wearing a prosthesis.A sensory feedback system contains sensors to detect signals applied to the prosthetics. The signals are encoded via signal processing to resemble the detected sensation delivered by actuators on the skin. There is a challenge in implementing commercial sensors in a prosthetic finger. Due to the prosthetic finger’s curvature and the fact that some prosthetic hands use a covering rubber glove, the sensor response would be inaccurate. This thesis shows that a pneumatic touch sensor integrated into a rubber glove eliminates these errors. This sensor provides a consistent reading independent of the incident angle of stimulus, has a sensitivity of 0.82 kPa/N, a hysteresis error of 2.39±0.17%, and a linearity error of 2.95±0.40%.For intuitive tactile stimulation, it has been suggested that the feedback stimulus should be modality-matched with the intention to provide a sensation that can be easily associated with the real touch on the prosthetic hand, e.g., pressure on the prosthetic finger should provide pressure on the residual limb. A stimulus should also be spatially matched (e.g., position, size, and shape). Electrotactile stimulation has the ability to provide various sensations due to it having several adjustable parameters. Therefore, this type of stimulus is a good candidate for discrimination of textures. A microphone can detect texture-elicited vibrations to be processed, and by varying, e.g., the median frequency of the electrical stimulation, the signal can be presented on the skin. Participants in a study using electrotactile feedback showed a median accuracy of 85% in differentiating between four textures.During active exploration, electrotactile and vibrotactile feedback provide spatially matched modality stimulations, providing continuous feedback and providing a displaced sensation or a sensation dispatched on a larger area. Evaluating commonly used stimulation modalities using the Rubber Hand Illusion, modalities which resemble the intended sensation provide a more vivid illusion of ownership for the rubber hand.For a potentially more intuitive sensory feedback, the stimulation can be somatotopically matched, where the stimulus is experienced as being applied on a site corresponding to their missing hand. This is possible for amputees who experience referred sensation on their residual stump. However, not all amputees experience referred sensations. Nonetheless, after a structured training period, it is possible to learn to associate touch with specific fingers, and the effect persisted after two weeks. This effect was evaluated on participants with intact limbs, so it remains to evaluate this effect for amputees.In conclusion, this thesis proposes suggestions on sensory feedback systems that could be helpful in future prosthetic hands to (1) reduce their complexity and (2) enhance the sense of body ownership to enhance the overall sense of embodiment as an addition to an intuitive control system

User Preferences for Calming Affective Haptic Stimuli in Social Settings

This paper presents a survey informing a user-first approach to designing calming affective haptic stimuli by eliciting user preferences in different social scenarios. Prior affective haptics research presented users with stimuli and recorded emotional responses. By contrast this work focuses on the sensations users wish to experience and how these can be simulated using haptics. The survey (n=81) investigated which users preferences in four social situations to reduce social anxiety. Using thematic analysis of responses we created a coding scheme of stimuli derived from real-world experiences to emulate with affective haptics. By cross-referencing these categories with affective haptics research, we provide recommendations to designers about which calming stimuli users wish to experience socially and how they can be implemented

Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

Developing a Labeled Affective Magnitude scale and Fuzzy Linguistic scale for tactile feeling

Affective design is the inclusion or representation of human emotions and subjective impressions in product design processes. In affective design, a number of different scales are commonly used to reveal and measure subjective emotions related to the design features of products. Osgood's Semantic Differential Scale (SDS) is one of the scales that has often been used for this purpose. However, there are some drawbacks in the SDS due to the ordinal nature of the scale that leads to losses or distortions of a significant amount of information and this makes it difficult to justify parametric statistical analysis. In this study, two scales, namely a Labeled Affective Magnitude (LAM) scale and a Fuzzy Linguistic scale, are developed. The LAM scale is an alternative scale based on magnitude estimation and has ratio properties. The Fuzzy Linguistic scale is an interval scale for which responses are linguistic descriptors that are identified with fuzzy numbers or intervals. The scales were developed for tactile feelings because they are an important factor in product evaluation. Statistical analysis was conducted to compare the scales. There was no significant difference between the newly constructed fuzzy scale and 11 point SDS, whereas there was a significant difference between the newly constructed LAM scale and 11 point SDS

Identificação de Características e Propriedades Morfológicas em Texturas Táteis: Estudo sobre Gráficos Educativos e Cartografias para Crianças com Deficiência Visual

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

Using Multivariate Pattern Analysis to Investigate the Neural Representation of Concepts With Visual and Haptic Features

A fundamental debate in cognitive neuroscience concerns how conceptual knowledge is represented in the brain. Over the past decade, cognitive theorists have adopted explanations that suggest cognition is rooted in perception and action. This is called the embodiment hypothesis. Theories of conceptual representation differ in the degree to which representations are embodied, from those which suggest conceptual representation requires no involvement of sensory and motor systems to those which suggest it is entirely dependent upon them. This work investigated how the brain represents concepts that are defined by their visual and haptic features using novel multivariate approaches to the analysis of functional magnetic resonance imaging (fMRI) data. A behavioral study replicated a perceptual phenomenon, known as the tactile disadvantage, demonstrating that that verifying the properties of concepts with haptic features takes significantly longer than verifying the properties of concepts with visual features. This study suggested that processing the perceptual properties of concepts likely recruits the same processes involved in perception. A neuroimaging study using the same paradigm showed that processing concepts with visual and haptic features elicits activity in bimodal object-selective regions, such as the fusiform gyrus (FG) and the lateral occipitotemporal cortex (LOC). Multivariate pattern analysis (MVPA) was successful at identifying whether a concept had perceptual or abstract features from patterns of brain activity located in functionally-defined object-selective and general perceptual regions in addition to the whole brain. The conceptual representation was also consistent across participants. Finally, the functional networks for verifying the properties of concepts with visual and haptic features were highly overlapping but showed differing patterns of connectivity with the occipitotemporal cortex across people. Several conclusions can be drawn from this work, which provide insight into the nature of the neural representation of concepts with perceptual features. The neural representation of concepts with visual and haptic features involves brain regions which underlie general visual and haptic perception as well visual and haptic perception of objects. These brain regions interact differently based on the type of perceptual feature a concept possesses. Additionally, the neural representation of concepts with visual and haptic features is distributed across the whole brain and is consistent across people. The results of this work provide partial support for weak and strong embodiment theories, but further studies are necessary to determine whether sensory systems are required for conceptual representation