A review of contemporary techniques for measuring ergonomic wear comfort of protective and sport clothing

Protective and sport clothing is governed by protection requirements, performance, and comfort of the user. The comfort and impact performance of protective and sport clothing are typically subjectively measured, and this is a multifactorial and dynamic process. The aim of this review paper is to review the contemporary methodologies and approaches for measuring ergonomic wear comfort, including objective and subjective techniques. Special emphasis is given to the discussion of different methods, such as objective techniques, subjective techniques, and a combination of techniques, as well as a new biomechanical approach called modeling of skin. Literature indicates that there are four main techniques to measure wear comfort: subjective evaluation, objective measurements, a combination of subjective and objective techniques, and computer modeling of human–textile interaction. In objective measurement methods, the repeatability of results is excellent, and quantified results are obtained, but in some cases, such quantified results are quite different from the real perception of human comfort. Studies indicate that subjective analysis of comfort is less reliable than objective analysis because human subjects vary among themselves. Therefore, it can be concluded that a combination of objective and subjective measuring techniques could be the valid approach to model the comfort of textile materials

Data-driven robotic manipulation of cloth-like deformable objects : the present, challenges and future prospects

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of compression strength while two points on the article are pushed towards each other and include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state–action dynamics as significant obstacles to perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth shaping, knot tying/untying, dressing and bag manipulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms.Publisher PDFPeer reviewe

QuintEssence: A Probe Study to Explore the Power of Smell on Emotions, Memories, and Body Image in Daily Life

Previous research has shown the influence of smell on emotions, memories, and body image. However, most of this work has taken place in laboratory settings and little is known about the influence of smell in real-world environments. In this paper, we present novel insights gained from a field study investigating the emotional effect of smell on memories and body image. Taking inspiration from the cultural design probes approach, we designed QuintEssence, a probe package that includes three scents and materials to complete three tasks over a period of four weeks. Here, we describe the design of QuintEssence and the main findings based on the outcomes of the three tasks and a final individual interview. The findings show similar results between participants based on the scent. For example, with cinnamon, participants experienced feelings of warmth, coziness, happiness, and relaxation; they recalled blurred memories of past moments about themselves and reported a general feeling of being calm and peaceful towards their bodies. Our findings open up new design spaces for multisensory experiences and inspire future qualitative explorations beyond laboratory boundaries

Extending Knowledge Graphs with Subjective Influence Networks for personalized fashion

International audienceThis chapter shows Stitch Fix's industry case as an applied fashion application in cognitive cities. Fashion goes hand in hand with the economic development of better methods in smart and cognitive cities, leisure activities and consumption. However, extracting knowledge and actionable insights from fashion data still presents challenges due to the intrinsic subjectivity needed to effectively model the domain. Fashion ontologies help address this, but most existing such ontologies are "clothing" ontologies, which consider only the physical attributes of garments or people and often model subjective judgements only as opaque categorizations of entities. We address this by proposing a supplementary ontological approach in the fashion domain based on subjective influence networks. We enumerate a set of use cases this approach is intended to address and discuss possible classes of prediction questions and machine learning experiments that could be executed to validate or refute the model. We also present a case study on business models and monetization strategies for digital fashion, a domain that is fast-changing and gaining the battle in the digital domain

Contributions for a new body representation paradigm in pattern design. Generation of basic patterns after the mobile body

Tese apresentada à Faculdade de Arquitectura de Lisboa da Universidade Técnica de Lisboa, para obtenção do grau de Doutor em Design

CBCRS: An open case-based color recommendation system

In this paper, a case-based color recommendation system (CBCRS) is proposed for online color ranges (CRs) recommendation. This system can help designers and consumers to obtain the most appropriate CR of consumer-products (e.g., garments, cars, architecture, furniture …) based on the color image perceptual data of each specific user. The proposed system is an open system, permitting to dynamically integrate new CRs by progressively learning from users’ and designers’ perceptual data. For this purpose, a Color Image Space (CIS) is initially established by using Basic Color Sensory Attributes (BCSAs) to obtain the color image perceptual data of both designers and consumers. Emotional Color Image Words (CIWs) representing CRs are measured in the proposed CIS through a knowledge-based Kansei evaluation process performed by designers using fuzzy aggregation operators and fuzzy similarity measurement tools. Using this method, new CIWs and related CRs from open resources (such as new color trends) can be integrated into the system. In a new recommendation, user's color image perceptual data measured in the proposed CIS regarding different BCSAs will be compared with those of CIWs previously defined in the system in order to recommend new CRs. CBCRS is an adaptive system, i.e. satisfied CRs will be further retained in a Successful Cases Database (SCD) so as to adapt recommended CRs to new consumers, who have similar user profiles. The general working process of the proposed system is based on case-based learning. Through repeated interactions with the proposed system by performing the cycle of Recommendation – Display - Evaluation – SCD adjustment, users (consumer or designer) will obtain satisfied CRs. Meanwhile, the quality of the SCD can be improved by integrating new recommendation cases. The proposed recommendation system is capable of dynamically generating new CIWs, CRs and new cases based on open resources.SMDTex Project funded by the European Erasmus Mundus Progra

ICS Materials. Towards a re-Interpretation of material qualities through interactive, connected, and smart materials.

The domain of materials for design is changing under the influence of an increased technological advancement, miniaturization and democratization. Materials are becoming connected, augmented, computational, interactive, active, responsive, and dynamic. These are ICS Materials, an acronym that stands for Interactive, Connected and Smart. While labs around the world are experimenting with these new materials, there is the need to reflect on their potentials and impact on design. This paper is a first step in this direction: to interpret and describe the qualities of ICS materials, considering their experiential pattern, their expressive sensorial dimension, and their aesthetic of interaction. Through case studies, we analyse and classify these emerging ICS Materials and identified common characteristics, and challenges, e.g. the ability to change over time or their programmability by the designers and users. On that basis, we argue there is the need to reframe and redesign existing models to describe ICS materials, making their qualities emerge

KEER2022

Avanttítol: KEER2022. DiversitiesDescripció del recurs: 25 juliol 202