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.

Background: In neurology and rehabilitation the primary interest for using wearables is to supplement traditional patient assessment and monitoring in hospital settings with continuous data collection at home and in community settings. The aim of this project was to develop a novel wearable garment with integrated sensors designed for continuous monitoring of physiological and movement related variables to evaluate progression, tailor treatments and improve diagnosis in epilepsy, Parkinson's disease and stroke. In this paper the early development and evaluation of a prototype designed to monitor movements and heart rate is described. An iterative development process 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 of garment design, functionality and usability. The project is a multidisciplinary collaboration with experts from medical, engineering, textile, and material science within the wearITmed consortium. The work was organized in regular meetings, task groups and hands-on workshops. User needs were identified using results from a mixedmethods systematic 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 content analysis. Results: The garment was well accepted by the users regarding design and comfort, although the users were cautious about the technology and suggested improvements. All electronic components passed a washability test. The most robust data was obtained from accelerometer and gyroscope sensors while the electrodes for heart rate registration were sensitive to motion artefacts. The algorithm development within the wearITmed consortium has shown promising results.

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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.

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.

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