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As people pay more attention to environmental issues, incorporating leather elements in solid wood furniture has become a new trend. This change reflects consumers’ concern for sustainable materials and their quest for personalized home design. Due to the similarity between styling of leather custom closets in the market, its surface texture and color are the key factors influencing consumers’ purchasing decisions. This study explored the visual-tactile perception of different leather materials by Chinese leather custom furniture consumers and establish an evaluation model. Based on Kansei engineering and market trend research, 12 representative leather samples and 7 perceptual phrases were selected through expert evaluation and KJ methods. Questionnaires were used to collect consumers’ visual-tactile perception evaluations of leather samples. Analysis using SPSS software showed that surface roughness, softness, and comfort of the material were the key factors affecting the tactile perception, while the visual perception was closely related to the color characteristics and aesthetic of the material. Cluster analysis categorized these materials as suitable for 4 different styles of home environments. This paper provides a theoretical basis for selecting materials for leather customized furniture and guides future design.

With the rise of the ‘her economy’, the influence of women’s consumer demand on furniture design is becoming increasingly important. The purpose of this study was to explore the relationship between female consumers’ visual and tactile perceptions of different wardrobe furniture materials and their psychological and sensory cognition. Based on the theory of Kansei engineering, a questionnaire was designed using a semantic differential scale and a seven-point Likert scale. Female participants were invited to rate 8 sets of perceptual vocabulary for 13 representative wardrobe furniture material samples through visual and tactile perception. SPSS 27 software was used to conduct reliability and validity tests, cluster analysis, and factor analysis on the experimental data. Cluster analysis categorized the materials into three types: natural flexible materials, patterned solid wood materials, and modern materials. Factor analysis identified two key dimensions: tactile perception and visual perception. These dimensions were used to analyze the differences in sensory cognition among the three material types in female consumers. This experiment provided theoretical support for the study of female consumers’ perceptual perception of wardrobe furniture materials, and at the same time provided rational references for designers to optimise the choice of materials in wardrobe furniture design based on the emotional needs of female users.

The inherent warmth of wood is widely valued in design applications, yet the mechanisms underlying its perception across different sensory modalities have not been fully explored. The aim of this work was to investigate the physical properties that influence warmth perception of wood across different species and surface treatments, and to clarify the respective contributions of visual and tactile warmth during multisensory integration. In this work, 10 material samples were technically characterized and their perceived warmth was evaluated by participants under three conditions: vision-only, touch-only, or combined visual-tactile interactions. Infrared thermography was used to quantify material temperature changes. Results showed that color dominated warmth perception under the visual assessment, while thermal properties and hand-material interface temperature differences significantly influenced tactile warmth perception. Wood species exhibited substantial effects on warmth perception, whereas surface treatments showed limited impact. Visual-tactile warmth perception was significantly positively correlated with both modalities, predominantly mediated by tactile inputs during direct contact, with visual characteristics providing critical complementary information. These findings advance the understanding of wood’s multisensory warmth perception and provide valuable insights for user-centered wood space and product design.

In the contemporary era of quality and personalization, this article explores how soft sofa fabrics enhance users’ emotional experience and convey perceptual images. Users’ visual-tactile perception data on 10 common soft sofa fabrics were gathered by questionnaire surveys, utilizing the Kansei engineering approach, and the visual-tactile evaluation theory. With SPSS software, the data were processed and examined in-depth using a variety of techniques, including cluster analysis and factor analysis. The experiment screened fabric samples and emotional vocabularies via the KJ method and expert evaluation, and questionnaires were designed and implemented based on the semantic differential method and Likert scale. Fabrics were categorized into four groups based on cluster analysis, which are suitable for users pursuing different home environments. The two primary factors that comprise the fundamental aspects of the perceptual image of soft sofa fabrics were found to be the texture, quality experience factor, and the typical emotional reaction factor, which were extracted by factor analysis. Both theory and practice were considered, enriching the theoretical framework of emotional imagery and user emotion research while offering valuable practical guidance for the design, production, and marketing of soft sofas.

In this study, the authors study a deep learning model that can convert vision into tactile information, so that different texture images can be fed back to the tactile signal close to the real tactile sensation after training and learning. This study focuses on the classification of different image visual information and its corresponding tactile feedback output mode. A training model of ensembled generative adversarial networks is proposed, which has the characteristics of simple training and stable efficiency of the result. At the same time, compared with the previous methods of judging the tactile output, in addition to subjective human perception, this study also provides an objective and quantitative evaluation system to verify the performance of the model. The experimental results show that the learning model can transform the visual information of the image into the tactile information, which is close to the real tactile sensation, and also verify the scientificity of the tactile evaluation method.

Virtual technologies such as haptic devices and virtual try-ons have been developed to bring more certainty to the non-touch shopping experience; however, they are still no substitute for the in-person experience. In order to resolve the current limitations of haptic technology, it is necessary to carry out fundamental research on the ways in which humans perceive and discern different tactile properties. This study investigated how vision and physical touch affect the evaluation of the tactile properties of knitwear and discovered factors that affect tactile evaluation in a non-touch environment. The result of this study proved that humans can perceive tactile properties similarly when they are able to physically touch the fabric, whether their vision is obstructed or not. However, participants were unable to accurately perceive the tactile properties of knitwear when they evaluated fabrics using only visual materials, especially stretchiness and flexibility. It is confirmed that a surface haptic experience could increase the accuracy of stretchiness and flexibility evaluations, but it did not help in the evaluations of fabric thickness and heaviness. Findings from interviews suggested that the shape, width and number of folds, density, and thickness of the yarn are all major factors that influence the tactile perception of knitwear when participants could only evaluate properties through on-screen visual materials. Findings from this study contributes to the improvement of the consumer experience in the contact-free shopping environment and can be used as a fundamental guide to human perception of clothing, which can support technologies such as haptic devices.