Fashion and Textiles最新文献

Occupational hand-arm vibration from powered hand tools is a common industry occurrence, which is remedied by using anti-vibration gloves. However, existing gloves often protect at the cost of reduced dexterity and increased muscular effort. This study examines how different palm padding layouts influence hand-related performance. Three anti-vibration glove prototypes are developed with identical material stacks but different neoprene palm paddings: segment-based, gradient, and proximal interphalangeal joint-oriented paddings. Female participants perform six representative hand-use tasks under bare-hand and gloved conditions, and the outcomes are evaluated using forearm surface electromyography, hand-performance measures, and subjective ratings. The results show that all three gloves reduce grip strength and slow down pegboard screwing, but largely preserve the key pinch strength compared to the bare hand. Among the three designs, the glove with the continuous gradient palm padding shows the most favorable overall pattern, with better preservation of dexterity-related performance and the smallest increase in forearm muscle activity. The segmented layout is more often associated with poorer dexterity and higher forearm muscle activity during repetitive tasks. In contrast, the proximal interphalangeal joint-oriented layout shows more task-dependent effects, particularly in externally supported or load-transfer tasks. These findings suggest that palm padding configuration can influence dexterity and physiological demand independently of material composition.

Online fashion platforms commonly organize products using broad hue labels such as red, blue, green, and yellow, although products within the same hue category may vary substantially in lightness and chroma. This study examines how within-hue color variation in online fashion assortments can be characterized using lightness–chroma (L*–C*) coordinates derived from the Commission Internationale de l’Éclairage L*a*b* color space (CIELAB). Product images were collected from a major South Korean online fashion retail platform using four hue-based knitwear queries, with 200 images retained for each hue query (N = 800). Garment regions were isolated using semantic segmentation, and dominant garment colors were extracted from CIELAB pixel values using MiniBatch K-means. The resulting L* and C* coordinates were analyzed using distributional analysis, data-adaptive K-means partitioning, and principal component analysis. Products retrieved under the same hue-based query occupied broad and differently configured regions of L*–C* space, with the four assortments differing in their lightness and chroma ranges and regions of product concentration. Data-adaptive partitioning summarized these within-hue distributions into distinct cluster configurations. An exploratory comparison using an additional 800 images collected approximately six months later further showed that changes in distributional location, dispersion, and overall L*–C* composition varied across hue-specific assortments. These findings demonstrate that nominal hue labels provide only a partial representation of color variation within online fashion assortments. The proposed framework provides a quantitative approach for characterizing and monitoring within-hue lightness–chroma composition, with potential applications in fashion assortment auditing, color planning, and more refined digital product organization.

Purpose

Mastectomy, though often lifesaving, can significantly impact physical and psychological well-being of women with breast cancer. Physical activity aids recovery, and supportive products such as external breast prostheses and sports bras play a key role; however, widespread user dissatisfaction suggests a mismatch between existing products and survivors' multidimensional needs. This study sought to comprehensively examine survivors’ lived experiences with breast prostheses and sports bras, to identify their unmet needs, and to inform future product and service innovation.

Methods

Seventeen breast-cancer survivors in Hong Kong participated in in-depth, semi-structured interviews, and the data were analyzed thematically to identify recurrent patterns and overarching themes.

Results

Four themes emerged. (1) Physiological comfort and functional requirements: participants reported heat discomfort, weight imbalance, and poor fit attributable to static designs. (2) Psychological and emotional well-being: supportive products played a critical role in restoring self-confidence and supporting exercise as a coping strategy, yet anxiety often hindered physical activity. (3) Behavioral adaptation and compromise: survivors modified activities and relied on external networks for guidance owing to product limitations. (4) Opportunities for innovation: user-driven recommendations included modular, breathable designs and a thoroughly restructured, professionalized fitting and support ecosystem.

Conclusions

Current products inadequately address the complex, intertwined physiological, psychological, and social needs of breast-cancer survivors. User-centered, co-designed solutions that prioritize adaptive comfort, supported by a professional service framework, are urgently needed to enhance quality of life and promote holistic recovery.

As part of the global effort to replace petroleum-based materials with sustainable alternatives, there is growing interest in enhancing the toughness of biological materials for durable textile applications. Functional composites derived from renewable sources, such as fungal hyphae, have attracted widespread attention. However, mushrooms remain comparatively underexplored, despite their rich natural polysaccharide content and favorable processability. Herein, we present a sustainable biocomposite derived from Agaricus bisporus (white button mushrooms) that achieves high mechanical toughness via sheet lamination and interfacial lubrication. The composite is fabricated via a simple aqueous processing route without the use of organic solvents, involving vacuum filtration and drying. The resulting bio-laminate exhibits a toughness of 1.94 ± 0.21 N/mm² and a tensile strength of 14.50 ± 3.15 N/mm² (values comparable to those of cow leathers). Structural analysis reveals that high-aspect-ratio mushroom-derived sheets stack to form a laminated architecture, while glycerol enables shear sliding between layers, providing energy dissipation under tensile loading. The material is biodegradable, regenerable by water-based reprocessing, and compatible with conventional sewing and product integration. This work introduces a strategy for producing soft, renewable composites with tailored mechanical properties, offering an eco-friendly alternative to petroleum-based synthetic leather and textile composites with potential for scalable production.

Graphical Abstract

This study develops a three-mode analytical typology (material, technical, and structural narrative integration) for comparing how industrial apparel designers translate narrative intent into the material fabric of garments; a fourth strategy, phygital, is advanced as a proposed extension. The typology emerges from a multiple-case study of four narrative-design projects at a Turkish apparel brand (KAFT), conducted within its registered Design Centre between January 2024 and June 2025. The analysis applies Practice-Based Design Research methodology within a sociosemiotic analytic lens, drawing on internal closeout reports, design briefs, production records, and product-page narratives. Three cases each occupy a distinct mode: a custom-developed canvas-textured woven fabric (material); a heavyweight knit engineered for integrated serigraphy and embroidery (technical); and a diagonal-panel tank with jacquard-woven external labelling and internal serigraphy replacing the conventional care label (structural). A three-piece capsule translating Blender-generated 3D digital assets to direct-printed textile surfaces instantiates the proposed phygital extension. The study further names a methodological contribution, the designer-side/user-side evidentiary asymmetry: the structural separation of what an industry-collaborative study can document (designer-side decisions) from what it can only claim (user-side or sustainability outcomes requiring instruments the brand does not deploy). A consumer-survey study of attachment, a longitudinal wardrobe study, and a comparative life-cycle assessment are specified as falsifiable follow-ups.

This study aimed to develop a moisture-responsive fabric system that can regulate ventilation without external power and to evaluate its ability to improve thermal comfort when applied to a ventilated garment (VG). Six composite fabrics were fabricated by laminating hydrophilic woven and knitted base materials with a hydrophobic polyurethane nanoweb (PUN). Physical characterization showed that increasing the number of PUN layers gradually increased the fabric thickness and weight, while microscopic observation confirmed that the nanowebs formed stable and continuous layers on the fabric surface. Among these, CK/PUN3 exhibited the highest moisture responsiveness, which was associated with the different moisture responses between the hydrophilic substrate and hydrophobic nanoweb, as well as the porous and flexible knitted structure. The selected fabric was incorporated into a hoodie-style VG with 10 flap-shaped inserts, including three on the front torso and seven on the upper back, while mesh fabrics were added to the hood and underarms to improve airflow. The garment, designed from a stretchable polyester/polyurethane fabric, was visualized in CLO 3D and physically prototyped. A sweating thermal manikin test under controlled climate conditions (35 ± 0.5 ℃, 40 ± 5% RH) demonstrated that the VG reduced intrinsic and total evaporative resistance by 7.50% and 2.17%, respectively, compared to the control garment. Regional heat flux increased by 26.78% in the abdomen, 18.59% in the chest, 7.68% in the head, and 4.14% in the back. These findings suggest that passive moisture-responsive garments can improve localized heat release and thermal comfort in high-temperature outdoor environments.

Wearable assistive gloves often present a trade-off between mechanical assistance and wearability due to bulky, externally mounted actuation systems. This study developed a textile-integrated hand assistive glove by structurally embedding twisted string actuator (TSA) tendon strings into a woven fabric module and evaluated how the textile module influenced assistance performance and user acceptance. By comparing two woven structures (1/1 plain and 3/1 twill), the plain weave structure was selected based on warp-direction mechanical requirements for TSA-driven actuation. Woven modules were fabricated with different weave densities, and a 6 ends-per-inch (epi) configuration was adopted to balance force transmission and frictional resistance during rotational TSA operation. Two module shapes were applied: a flat-type module that is attached to the palmar fingertip and a round-type module enclosing the fingertip in a tapered thimble form. Ten adult male participants evaluated the gloves under four conditions (flat-type, round-type, commercial pneumatic glove, and bare hands). Design perception was assessed using eye tracking and design related questionnaires, assistance performance was evaluated using surface electromyography (sEMG) during a 12 kg static holding task, and wearability was examined using electroencephalography (EEG), clothing pressure, and subjective questionnaires during repetitive object-handling tasks. The sEMG results normalized to the bare-hand reference showed reduced muscle activation for the round type (74.14% RVC) and flat type gloves (85.26% RVC), whereas the pneumatic glove showed a slight increase (105.92% RVC). EEG results did not differ significantly across conditions, while clothing pressure differed across glove types, with the pneumatic glove exhibiting the highest mean pressure. Despite generating higher clothing pressure than the flat type glove, the round type glove received higher ratings for perceived functionality and purchase/use intention, indicating that wearability is not determined solely by physical pressure but is influenced by perceived functional effectiveness. The findings demonstrate that woven module shape plays a decisive role in balancing mechanical assistance and user acceptance, providing experimentally grounded design guidelines for textile-integrated assistive gloves.

Despite the growing adoption of augmented reality (AR) in online fashion retail, limited understanding exists regarding how specific AR features influence different dimensions of customer engagement behavior (CEB). Addressing this gap, this study examines the effects of key AR features—realism, interactivity, personalization, and usability—on participation, advocacy, and co-creation behaviors. Drawing on the stimulus–organism–response framework and flow theory, this study investigates the mediating role of psychological immersion and the moderating role of self-regulatory focus. Using survey data from 865 consumers in China, and Partial Least Squares–Structural Equation Modeling, the findings reveal that AR features significantly enhance consumers’ psychological immersion, which in turn strengthens advocacy and co-creation behaviors. While AR features also directly influence multiple engagement dimensions, their effects vary across behavioral outcomes. Psychological immersion serves as a key explanatory mechanism linking AR features to engagement. This study contributes by conceptualizing CEB as a multidimensional construct and by demonstrating that AR features operate through differentiated psychological pathways. By integrating psychological immersion and self-regulatory focus, the findings provide a more nuanced understanding of how and under what conditions AR drives customer engagement in online fashion retail.

With the rapid diffusion of AIGC technologies, the fashion industry has entered a new phase of technology-enabled transformation across multiple application scenarios. Using a Systematic Literature Review approach, this study analyzes 163 publications retrieved from Web of Science, EBSCO, IEEE Xplore, and Scopus to examine the research landscape, technological pathways, thematic focuses, and future directions of AIGC in fashion. The results indicate that related research has grown rapidly since 2022, forming an overall international trend of multi-center distribution and broad participation; relevant studies are widely distributed in interdisciplinary journals, and empirical case studies and quantitative research are currently the dominant paradigms. The technological evolution reveals a gradual paradigm shift from GAN-based approaches toward Diffusion Models and Large Language Models (LLMs). Research themes primarily focus on Intelligent Design & Customization, Trend Forecasting & Consumer Behavior, AI & Fashion Education, Law & Ethics, and Sustainable Fashion Design; furthermore, based on qualitative analysis, a three-layer framework of "Application–Design–Attribute" is constructed to elucidate the advantages and risks of AIGC in the fashion industry. Finally, this study proposes future research agendas such as advancing the three-layer architecture and building multi-agent collaborative systems. This research contributes to a deeper understanding of how AIGC empowers the fashion industry and provides a reference for related research.