166,221 research outputs found

    Functional textile preferences of elderly people

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    Aging is an inevitable stage of lifetime bringing along physical and emotional deterioration. Rate of aging population in the world has been constantly rising with the contribution of technological improvements on life quality, and medical services. Depending on the unavoidable physical and emotional changes of aging human body, clothing preferences and needs become different then needs of other textile and clothing consumer groups. Textile and clothing products are one of the basic needs of human kind. Sufficient and appropriate clothing is especially important for life quality improvement at elderly stage of human life. New generation functional and smart textile and clothing products bring new opportunities to improve life quality of elderly people with such wide range products of mobility support clothing, medical help, hygiene, and health monitoring textile and clothing products. This survey based research work is aimed to search the awareness level and priority of society about the functional and smart textile products for elderly people. It has been found that gender difference has significant influence on preference level of functional textile products, where women has higher interest then men about functional textiles. It can also be stated that comfort properties are primarily preferred preferences comparing to the fashion and functionality properties of textile products. © 2015, Mediterranean Center of Social and Educational Research. All rights reserved

    The future design direction of smart clothing development

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    Literature indicates that Smart Clothing applications, the next generation of clothing and electronic products, have been struggling to enter the mass market because the consumers’ latent needs have not been recognised. Moreover, the design direction of Smart Clothes remains unclear and unfocused. Nevertheless, a clear design direction is necessary for all product development. Therefore, this research aims to identify the design directions of the emerging Smart Clothes industry by conducting a questionnaire survey and focus groups with its major design contributors. The results reveal that the current strategy of embedding a wide range of electronic functions in a garment is not suitable. This is primarily because it does not match the users’ requirements, purchasing criteria and lifestyle. The results highlight the respondents’ preference for personal healthcare and sportswear applications that suit their lifestyle, are aesthetically attractive, and provide a practical function

    Study on research mode of smart safety outfits system for children

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    According to the special characteristics of children’s body and mind and the concept of human–computer interaction, the research and development model of children’s intelligent safety clothing is explored and a A practical research model. Based on the multi–dimensional needs of consumers for children’s clothing and the performance of smart components, we explore the combination of smart wearable equipment and children’s safety clothing, and propose a design process architecture that takes into account function and aesthetics. Through the analysis of the connection technology between smart clothing and mobile terminals, we propose the idea from single interaction to multi–device co–connection, and establish a multi–interaction smart clothing based on the optimal allocation of energy and high. Through the analysis of the connection technology between smart clothing and mobile terminals, we propose the idea of moving from single interaction to multi–device co–connection, and establish the R&D process of multi–interaction smart wearable devices based on optimal energy allocation and efficient information transmission

    Research and analysis of user needs for smart clothing for the elderly

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    Following the principle of “people-oriented”, we explore the user needs of smart clothing for the elderly and provide reference for the development of such clothing. The target consumers of smart clothing for the elderly are divided into two categories: The elderly and the young, and the needs of elderly users are investigated by means of literature analysis and interviews. The study showed that the needs of elderly users for senior smart clothing can be divided into five areas: Physiological, psychological, aesthetic, functional and consumer; the younger group is generally willing to buy senior smart clothing for the elderly and wants functional design to focus on physiological monitoring technology and aesthetic design to focus on loose fit design and dark shades of colour matching. The findings of the study will help companies to improve their design solutions and promote the healthy development of the senior clothing market

    Female bike riders’ clothing needs with the incorporation of wearable technology: Design and evaluation of wearers’ perception of smart clothing within the cradle-to-cradle design framework

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    The overall purpose of this study was to increase a general understanding of the mechanisms that determine how female bike riders’ clothing needs are met through the use of smart clothing, by empirically testing new smart clothing designs that incorporate wearable devices developed by the researcher within the cradle-to-cradle design framework. The specific objectives of this study were: (1) to identify important design criteria of bike wear for female bike riders under the frame of consumers’ functional-expressive-aesthetic needs along with their needs and desires for wearable technology; (2) to design and develop smart clothing for female bike riders in accordance with identified female bike riders’ expectations and needs within the cradle-to-cradle design framework; (3) to evaluate female bike riders’ perceived needs satisfaction and social acceptability of the proposed smart clothing by examining the relationships among perceived satisfaction of functional, expressive and aesthetic needs, and perceived social acceptability; and (4) to evaluate the marketability of proposed smart clothing by testing the hypothetical research model incorporating the following variables: perceived satisfaction of functional, expressive and aesthetic needs, perceived social acceptability, attitude, and purchase intention. The findings of this study were based on data collected from two different online surveys (Study 1 and Study 2) as well as a proposed smart bike jacket that included transformable functions developed by this researcher and used for Study 2 survey. For this study, females in large cities worldwide were considered a key segment of the population for studying female bike riders’ clothing needs incorporating wearable technologies. Using a purposeful and convenience sampling approach, the Study 1 sample was recruited from females aged 18 years and over living in the U.S. with bike riding experience, and were members of the “Transportation Alternative,” a non-profit organization dedicated to bike riders in New York City; 136 usable responses were obtained and used for the data analysis. The Study 2 used a nation-wide convenience sampling approach that involved females aged 18 years and over living in the U.S. with bike riding experiences; 488 usable responses were obtained from the Amazon Mechanical Turk and used for the data analysis. The instrumentation for the study incorporated two main online questionnaires, including both close-ended and open-ended questions, and proposed smart bike wear developed by the researcher. Based on female bike riders’ identified bike wear needs from Study 1 survey, the researcher incorporated appropriate design components into smart clothing design incorporating a wearable device for addressing survey participants’ special needs. The developed smart bike wear in this stage was used for Study 2 survey. Two self-administered questionnaires for the Study 1 and Study 2 were developed using multiple-item measurements that were validated and determined as reliable from previous studies and open-ended questions. In Study 2 survey, the participants were expected to respond to each question after watching a short video clip demonstrating the features of the proposed smart clothing, as a tool of stimuli to measure perception of respondents toward the proposed smart clothing. The Statistical Package for the Social Sciences (SPSS Version 21.0) software and AMOS Version 21.0 were employed to conduct statistical analyses and model testing. Demographic data were analyzed using descriptive statistics for both the 136 respondents for the Study 1 and the 488 respondents for the Study 2. An initial series of confirmatory factor analysis (CFA) was used to test validity and reliability of constructs in the measurement model for both the Study 1 and Study 2. In the Study 2, the structural equation model for theoretical predictors of purchase intention was tested. To analyze the data collected from open-ended questions, the researcher used a word clouds analysis, a popular content analysis method for text-based data. The findings were: 1. The Study 1 identified 25 valid functional-expressive-aesthetic-price (FEAP) needs measurement items that were applicable for consideration when designing smart clothing from the perspective of female bike riders. Functional design characteristics, especially those contributing to comfort, protection, and ventilation, were the most important needs of respondents. Expressive and aesthetic design characteristics were also shown to be important needs to be considered when designing female bike riders’ clothing, but less important than functional needs. 2. Smart clothing that embedded multiple transformable features was favored by most respondents, and a jacket that could be changed into a bag was the most commonly desired transformable smart clothing feature. The findings from Study 1 survey guided this researcher to design a smart jacket transformable into a bag capable of storing detachable pieces, with essential design characteristics that incorporated identified consumers’ bike wear design needs. The processes of product design and development were guided by the frame of the cradle-to-cradle (C2C) design process which fully considered sustainability practices. A female bike riders’ transformable jacket incorporating a LED signal lighting device was developed in response to participants’ needs and desires that were identified in the Study 1. 3. The Study 2 identified 41 valid functional-expressive-aesthetics (FEA), social acceptability, attitude, and purchase intention related measurement items to examine respondents’ perceived satisfaction level for the proposed smart jacket. The proposed smart bike wear fulfilled the functional needs across all elements for smart bike wear. Especially, the results proved that ventilation features (e.g., mesh trimmed around armpits, detachable sleeves), as well as enhanced visibility (e.g., incorporated reflective trimming and a LED lighting device) of the proposed smart clothing satisfied consumers’ special smart clothing needs when bike riding. The proposed smart jacket also fulfilled the aesthetic and expressive needs of the respondents. Regarding social acceptance of the proposed smart clothing, most of the respondents said that what was presented in smart clothing was socially acceptable. A few responses suggested there were privacy concerns about wearable devices that use smart phone applications to collect data. 4. The hypothesized model consisted of six latent variables (functional design characteristics, expressive design characteristics, aesthetic design characteristics, social acceptability, attitudes, and purchase intention). The results of structural equation modeling (SEM) for the hypothesized model revealed a good model fit. All five structural paths in the model were statistically significant. As expected from hypothesis (H) 1, perceived satisfaction of functional design characteristics significantly and positively affected attitude; for H2, perceived satisfaction of expressive design characteristics significantly and positively affected attitude; for H3, perceived satisfaction of aesthetic design characteristics significantly and positively affected attitude; for H4, perceived social acceptability significantly and positively affected attitude; and for H5, attitude toward purchasing smart clothing significantly and positively affected purchasing intention. The statistical testing results confirm that the level of perceived satisfaction of functional, expressive, and aesthetic design characteristics as well as perceived social acceptability influences the creation of positive attitudes toward the use of smart clothing, leading to positive purchase intentions for smart clothing. This research significantly contributes to the literature by providing insight into the inadequately researched area of smart clothing for female bike riders. It is the first study conducted that investigated female bike riders’ special needs and social acceptability of smart clothing under the C2C design framework. Its holistic approach to the analysis of data collected through various research stages (needs identification-smart clothing design-design evaluation) uncovered previously unidentified issues surrounding female bike riders’ smart clothing needs, revealing numerous areas where future research is needed, and providing vital information for both the apparel industry and academia. Limitations of this study were presented, and implications and recommendations for future studies and for practice were also suggested

    Comparing clothing-mounted sensors with wearable sensors for movement analysis and activity classification

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    Inertial sensors are a useful instrument for long term monitoring in healthcare. In many cases, inertial sensor devices can be worn as an accessory or integrated into smart textiles. In some situations, it may be beneficial to have data from multiple inertial sensors, rather than relying on a single worn sensor, since this may increase the accuracy of the analysis and better tolerate sensor errors. Integrating multiple sensors into clothing improves the feasibility and practicality of wearing multiple devices every day, in approximately the same location, with less likelihood of incorrect sensor orientation. To facilitate this, the current work investigates the consequences of attaching lightweight sensors to loose clothes. The intention of this paper is to discuss how data from these clothing sensors compare with similarly placed body worn sensors, with additional consideration of the resulting effects on activity recognition. This study compares the similarity between the two signals (body worn and clothing), collected from three different clothing types (slacks, pencil skirt and loose frock), across multiple daily activities (walking, running, sitting, and riding a bus) by calculating correlation coefficients for each sensor pair. Even though the two data streams are clearly different from each other, the results indicate that there is good potential of achieving high classification accuracy when using inertial sensors in clothing

    Smart Textiles and Clothing: An Opportunity or a Threat for Sustainability?

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    Wearable technology products which include smart clothing and textiles have grown in popularity and are only expected to become more ubiquitous over the next several years with an annual growth of 23 percent reaching 100billioninsalesby2023and100 billion in sales by 2023 and 150 billion by 2026. But this growing demand does not come without considerable cost. Combining electronics and textiles, which both are relatively short-lived mass consumer goods, would intensify product obsolescence and lead to even shorter life cycles and abandonment of products. Although there is extensive research on the sustainability of fashion, limited research exists on the sustainability of smart textiles and clothing, and it appears timely and significant for an exploratory study on this topic. This study explores sustainability of smart textiles and clothing by a critical and in-depth review of existing literature and recent design efforts in the industry and in alternative realms such as maker spaces. The study introduces design approaches for more sustainable products and user experiences by employing Norman’s levels of emotional design [1], and Lamb and Kallal’s functional, expressive, and aesthetic (FEA) apparel design models [2] as grounding frameworks to discuss the sustainability of smart textiles and clothing from all angles. References [1] Norman, Donald A. 2004. Emotional design: Why we love (or hate) everyday things. Basic Civitas Books. [2] Lamb, Jane M., and M. Jo Kallal. 1992. A conceptual framework for apparel design. Clothing and Textiles Research Journal 10, 2, (1992), 42-47. </div
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