Prolonging garment longevity is a well-recognized key strategy to reduce the overall environmental impact in the textile and clothing sector. In this context, change or degradation in esthetic or visual appeal of a garment with usage is an important factor that largely influence its longevity. Therefore, to engineer the garments for a required lifetime or prolong longevity, there is a need for predictive systems that can forecast the trajectory of visual degradation based on material/structural parameters or use conditions that can guide the practitioners for an optimal design. This paper develops a deep learning based predictive system for washing-induced visual change or degradation of selected garment areas. The study follows a systematic experimental design to generate and capture visual degradation in garment and equivalent fabric samples through 70 cycles in a controlled environment following guideline from relevant washing standards. Further, the generated data is utilized to train conditional Generative Adversarial Network-based deep learning model that learns the degradation pattern and links it to washing cycles and other seam properties. In addition, the predicted results are compared with experimental data using Frechet Inception Distance, to ascertain that the system prediction are visually similar to the experimental data and the prediction quality improves with training process.

Background: In neurology and rehabilitation the primary interest for using wearables is to supplement traditionalpatient assessment and monitoring in hospital settings with continuous data collection at home and in communitysettings. The aim of this project was to develop a novel wearable garment with integrated sensors designed forcontinuous monitoring of physiological and movement related variables to evaluate progression, tailor treatmentsand improve diagnosis in epilepsy, Parkinson’s disease and stroke. In this paper the early development andevaluation of a prototype designed to monitor movements and heart rate is described. An iterative developmentprocess and evaluation of an upper body garment with integrated sensors included: identification of user needs,specification of technical and garment requirements, garment development and production as well as evaluation ofgarment design, functionality and usability. The project is a multidisciplinary collaboration with experts frommedical, engineering, textile, and material science within the wearITmed consortium. The work was organized inregular meetings, task groups and hands-on workshops. User needs were identified using results from a mixedmethodssystematic review, a focus group study and expert groups. Usability was evaluated in 19 individuals(13 controls, 6 patients with Parkinson’s disease) using semi-structured interviews and qualitative contentanalysis.

Results: The garment was well accepted by the users regarding design and comfort, although the users werecautious about the technology and suggested improvements. All electronic components passed a washabilitytest. The most robust data was obtained from accelerometer and gyroscope sensors while the electrodes forheart rate registration were sensitive to motion artefacts. The algorithm development within the wearITmedconsortium has shown promising results.

Conclusions: The prototype was accepted by the users. Technical improvements are needed, but preliminarydata indicate that the garment has potential to be used as a tool for diagnosis and treatment selection andcould provide added value for monitoring seizures in epilepsy, fluctuations in PD and activity levels in stroke.Future work aims to improve the prototype further, develop algorithms, and evaluate the functionality andusability in targeted patient groups. The potential of incorporating blood pressure and heart-rate variabilitymonitoring will also be explored.

Close to 30% of garments bought online are returned, often due to issues of fit. These issues often relate to size selection, which is challenging without physically trying on a garment. Alternative methods need to be explored to select the best size in lieu of physically trying apparel on. To address this issue, we compare the size selections based on primary measurements and size charts, virtual garments, and real garments. A cross-sectional quantitative survey was carried out in an experimental setting. The participants (36, predominantly White females, aged 21–56) made size selections and evaluations based on virtual and real blouses and trousers. Selecting the size based on virtual garments is more accurate than size selection based on primary measurements and size charts, scoring 57% and 42%, respectively. Further research should be used to improve the virtual fitting room, with benefits such as fewer returns and more satisfied customers.

Wearable Electrocardiography (ECG) sensing textiles have been widely used due to their high flexibility, comfort, reusability and the possibility to be used for home-based and real-time measurements. Textile electrodes are dry and non-adhesive, therefor unlike conventional gel electrodes, they don't cause skin irritation and are more user-friendly especially for long-term and continuous monitoring outside the hospital. However, the challenge with textile electrodes is that the quality and reliability of recorded ECG signals by smart garments are more sensitive to different factors such as electrode placement, skin humidity, user activities and contact pressure. This review will particularly focus on the research findings regarding the influence of electrode placement on the quality of biosignal sensing, and will introduce the methods used by researchers to measure the optimal positions of the electrodes in wearable ECG garments. The review will help the designers to take into account different parameters, which affect the data quality, reliability and comfort, when selecting the electrode placement in a wearable ECG garment.

Recording high quality biosignals by dry textile electrodes is a common challenge in medical health monitoring garments. The aim of this study was to improve skin–electrode interface and enhance the quality of recorded electrocardiography (ECG) signals by modification of textile electrodes embedded in WearItMed smart garment. The garment has been developed for long-term health monitoring in patients suffering from epilepsy and Parkinson’s disease. A skin-friendly electro-conductive elastic paste was formulated to coat and modify the surface of the knitted textile electrodes. The modifications improved the surface characteristics of the electrodes by promoting a more effective contact area between skin and electrode owing to a more even surface, fewer pores, greater surface stability against touch, and introduction of humidity barrier properties. The modifications decreased the skin–electrode contact impedance, and consequently improved the recorded ECG signals obviously when low pressure was applied to the electrodes, therefore contributed to greater patient comfort. The created contact surface allowed the natural humidity of the skin/sweat to ease the signal transfer between the electrode and the body, while introducing a shorter settling time and retaining moisture over a longer time. Microscopic images, ECG signal measurements, electrode–skin contact impedance at different pressures and times, and water absorbency were measured and reported.

Purpose

The purpose of this paper is to use a systematic model for detecting misfit between the garment and the target group.

Design/methodology/approach

Using an empirical–analytical methodology, the systematic model was tested. The input data were run through the model to generate the output data, which were analysed, including basic statistics. The purpose of the analysis was to detect misfit and improve the garment measurement chart. This procedure was repeated until a clear result was reached.

Findings

The result of this study is an optimised garment measurement chart, which considers the garment’s ease, different sizes/proportions in relation to a target group. The results show that it is possible to use a systematic model to define the shortcomings of a garment´s range of sizes and proportions.

Research limitations/implications

Further studies are needed to verify the results of the theoretical garment fit and their values in relation to real garment fit.

Practical implications

If the systematic model is implemented to improve the theoretical garment fit, this may have effects on the available garment sizes and its proportions, resulting in increased theoretical garment fit for the target group.

Originality/value

The paper presents a systematic model for detecting and eliminating theoretical fitting; the model includes both garment ease allowance and defined points of misfit.

Clothes affect everyone; we wear them for all occasions; they silently communicate on our behalf, and they can enhance our level of confidence and comfort. For the garment to be comfortable, the garment fit has to be appropriate. Appropriate for the intended function and in line with the wearer’s preferences. For the garment to end up as an approved garment in the customer’s wardrobe, it has to be improved and evaluated many times over. The final evaluation to pass is when the customer finds the garment, tries it on and asks: Does it really fit? The common denominator for the studies included in this thesis is garment fit; the goal is to investigate some methods to improve, find and evaluate garment fit. To improve garment fit, two studies were done. One study is on improving garment fit with the help of a systematic model, based on anthropometric and garment numerical data; this is explored with the help of an experimental set up. The second study is on improving garment fit for the unique figure by offering made-to-measure garments, which is investigated with a structure of action research. An experimental strategy is used to find garments that fit, where the size and fit correspondence is compared between virtual and real garments. To tie everything together, variables for garment fit evaluation are identified with the help of a structured literature review and then analysed within each study. The result shows that the theoretical garment fit improves by using the systematic model. Both the overall accommodation for the target group increased as well as the fit value. The garment fit is improved for the unique figure; this is achieved through complex body measurements, invasive pattern modifications and garment make-up for fit evaluation. The accuracy for size selection based on virtual garments exceeded the one based on the more traditional key measurements. The variables involved in the garment fit evaluation can be divided into five areas: influencing factors, evaluations focus, resources, evaluators or fitting sessions.

This is the final product construction report for the From Roll to Bag project. The purpose of this report is to present the implementation of the new pattern technology to selected products and to present the modularity for consumer selection. For fulfilling the tasks (5.1 and 5.2) two garments where chosen, one jacket and one shirt, and customization options regarding fit, model, colour and function were developed for each of them. This includes implementation of novel pattern technology to products, graphics, a product architecture with customisation options and initial production tests to verify perfect fit in production and later in use. The more challenging part was to guarantee manufacturability as the patterns require automated manufacturing equipment due to their detailed construction and the pattern matching. Such equipment includes a cutter with a scanner that identifies the outline of the printed pattern and cuts accoringly. If garments with less detailed graphics are considered for production, pre-dyed fabrics can be used and that requires less investments in manufacturing equipment. Such set up would miss one point of the project but in the tradeoff between investment cost and product price point it may be a viable solution. The garments and customization modules are also fit for production but in order to achieve a detailed production evaluation with exact production times and material consumption a long run of products is needed. Considerations about customer’s experiences in this type value chains are also discussed.