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In recent years, textile sensors have played a crucial role in the development of smart clothing, which integrates electronic components and technology into garments. Furthermore, a variety of textile sensors in smart clothing have gained attention for their healthcare applications, including analyzing sweat, monitoring biomarkers, and sensing electrophysiology. The conductive polymer poly (3,4‐ethylene dioxythiophene): polystyrene sulfonate (PEDOT:PSS) has been explored for various applications, such as flexible and wearable electronics, neural interfaces, and bioelectronics devices. Herein, a sensitive and selective ion detection utilizing cotton yarn‐based textile sensors integrated with ion‐selective membranes (ISMs) is presented. First, a straightforward and reproducible approach for manufacturing textile sensors based on PEDOT:PSS is described. The relationship between the resistance change of these sensors and their performance, encompassing stability and flexibility is investigated. Following this, ISMs are integrated into the sensors to detect sodium (Na+) and potassium (K+) ions, separately. The sensors display a consistent linear response toward the detected ion in a concentration range from 1 to 50 mM. Moreover, the sensors exhibit notable selectivity against the undesired ion. [ABSTRACT FROM AUTHOR]

This paper identifies and analyses current clothing options available to rock climbers in New Zealand, drawing from data collected via a survey of experienced climbers, relevant literature and a detailed design analysis of garments that are currently on the market. The study considers some of the limitations of current rock-climbing clothing and identifies issues that need to be taken into account to design more practical, responsive, sustainable clothing options for climbers. Drawing on professional design expertise in patternmaking, material selection and garment construction, this analysis is used to inform the development of more appropriate and innovative garment design strategies for rock-climbing. It also recognises the potential for novel development by employing innovations from the field of advanced textiles and apparel, in particular the integration of smart sensing technologies into garments. [ABSTRACT FROM AUTHOR]

Despite the potential of smart clothing, which allows collecting and processing data about the user's conditions and reactions, the environment in which they are inserted and connecting with other artifacts around them, aiming to facilitate daily activities and improve quality of life, problems environmental issues already faced by the clothing sector can be worsened due to the incorporation of electronic components in clothing. Design can contribute to reversing this situation through interventions within the scope of the concept of these products as well as in the associated services and systems. This article presents a review of the state of the art on the topic, with an emphasis on identifying the main environmental impacts and challenges of smart clothing from the perspective of the product life cycle, to contribute to the informational quality of the Designers involved in the project of this product category.

Abstract Background Wearable devices have the advantage of always being with individuals, enabling easy detection of their movements. Smart clothing can provide feedback to family caregivers of older adults with disabilities who require in-home care. Methods This study describes the process of setting up a smart technology-assisted (STA) home-nursing care program, the difficulties encountered, and strategies applied to improve the program. The STA program utilized a smart-vest, designed specifically for older persons with dementia or recovering from hip-fracture surgery. The smart-vest facilitated nurses’ and family caregivers’ detection of a care receiver’s movements via a remote-monitoring system. Movements included getting up at night, time spent in the bathroom, duration of daytime immobility, leaving the house, and daily activity. Twelve caregivers of older adults and their care receiver participated; care receivers included persons recovering from hip fracture (n = 5) and persons living with dementia (n = 7). Data about installation of the individual STA in-home systems, monitoring, and technical difficulties encountered were obtained from researchers’ reports. Qualitative data about the caregivers’ and care receivers’ use of the system were obtained from homecare nurses’ reports, which were explored with thematic analysis. Results Compiled reports from the research team identified three areas of difficulty with the system: incompatibility with the home environment, which caused extra hours of manpower and added to the cost of set-up and maintenance; interruptions in data transmissions, due to system malfunctions; and inaccuracies in data transmissions, due to sensors on the smart-vest. These difficulties contributed to frustration experienced by caregivers and care receivers. Conclusions The difficulties encountered impeded implementation of the STA home nursing care. Each of these difficulties had their own unique problems and strategies to resolve them. Our findings can provide a reference for future implementation of similar smart-home systems, which could facilitate ease-of-use for family caregivers.

Smart clothing encompass research in interdisciplinary fields such as industrial design, material applications, computer science, and medical services, and have witnessed rapid development over the past decade. Therefore, for scholars, keeping pace with emerging research trends and the evolution of knowledge is crucial. However, due to the wide array of disciplines involved in smart clothing and the wealth of information they encompass, scholars find it challenging to comprehensively grasp the knowledge structure, making it a time-consuming and highly complex task to identify the forefront of research hotspots. To provide a deeper insight into the knowledge framework and emerging trends in the field of smart clothing, this study is based on bibliometric analysis methods. It combines these methods with visualization analysis tools such as Citespace, VOSviewer, Scimago Graphica, and the AntConc corpus analysis tool. First, a dataset comprising 30,860 SCI papers, including research and review papers is collected. Secondly, a comprehensive analysis is conducted using co-occurrence analysis, core citation analysis, core collaboration analysis, and cutting-edge research analysis. Finally, a systematic knowledge framework for smart clothing is constructed. This study combines quantitative text analysis with knowledge visualization analysis to construct a more diverse and detailed knowledge map of smart clothing from multiple perspectives. Simultaneously, it tracks and summarizes the development of smart clothing, providing researchers in the field with a systematic research context and analysis of emerging trends. [ABSTRACT FROM AUTHOR]

Background: Wearable devices have the advantage of always being with individuals, enabling easy detection of their movements. Smart clothing can provide feedback to family caregivers of older adults with disabilities who require in-home care. Methods: This study describes the process of setting up a smart technology-assisted (STA) home-nursing care program, the difficulties encountered, and strategies applied to improve the program. The STA program utilized a smart-vest, designed specifically for older persons with dementia or recovering from hip-fracture surgery. The smart-vest facilitated nurses' and family caregivers' detection of a care receiver's movements via a remote-monitoring system. Movements included getting up at night, time spent in the bathroom, duration of daytime immobility, leaving the house, and daily activity. Twelve caregivers of older adults and their care receiver participated; care receivers included persons recovering from hip fracture (n = 5) and persons living with dementia (n = 7). Data about installation of the individual STA in-home systems, monitoring, and technical difficulties encountered were obtained from researchers' reports. Qualitative data about the caregivers' and care receivers' use of the system were obtained from homecare nurses' reports, which were explored with thematic analysis. Results: Compiled reports from the research team identified three areas of difficulty with the system: incompatibility with the home environment, which caused extra hours of manpower and added to the cost of set-up and maintenance; interruptions in data transmissions, due to system malfunctions; and inaccuracies in data transmissions, due to sensors on the smart-vest. These difficulties contributed to frustration experienced by caregivers and care receivers. Conclusions: The difficulties encountered impeded implementation of the STA home nursing care. Each of these difficulties had their own unique problems and strategies to resolve them. Our findings can provide a reference for future implementation of similar smart-home systems, which could facilitate ease-of-use for family caregivers. [ABSTRACT FROM AUTHOR]

Intense physical activity and high ambient temperature cause construction workers to be exposed to an increased risk of overheating, especially in the summer season. Personal cooling systems have great potential to support workers' thermoregulation and reduce this risk. In particular, solutions based on the thermoelectric effect can provide high cooling effectiveness and ergonomics at the same time. In this paper, a newly developed active clothing solution with flexible thermoelectric modules intended for outdoor activities is presented. The active clothing was subjected to utility tests on a treadmill under laboratory conditions with the participation of potential end users. A comparison of results from cooled and uncooled places indicated a reduction in local skin temperature of as much as 2.7 °C. Moreover, a gradual decrease in temperature in the uncooled place during the experiment was observed. Based on the positive results from this evaluation, the personal cooling system was integrated into active clothing within the ASSIST-IoT NGIoT reference architecture. This allows contextual and personalized adjustment of the cooling power to be provided using AI techniques and, additionally, by using data from a weather station and a smartwatch. Training procedures and models for the AI system are proposed, with special attention paid to the privacy aspect. [ABSTRACT FROM AUTHOR]

Monitoring human movement is highly relevant in mobile health applications. Textile-based wearable solutions have the potential for continuous and unobtrusive monitoring. The precise estimation of joint angles is important in applications such as the prevention of osteoarthritis or in the assessment of the progress of physical rehabilitation. We propose a textile-based wearable device for knee angle estimation through capacitive sensors placed in different locations above the knee and in contact with the skin. We exploited this modality to enhance the baseline value of the capacitive sensors, hence facilitating readout. Moreover, the sensors are fabricated with only one layer of conductive fabric, which facilitates the design and realization of the wearable device. We observed the capability of our system to predict knee sagittal angle in comparison to gold-standard optical motion capture during knee flexion from a seated position and squats: the results showed an R2 coefficient between 0.77 and 0.99, root mean squared errors between 4.15 and 12.19 degrees, and mean absolute errors between 3.28 and 10.34 degrees. Squat movements generally yielded more accurate predictions than knee flexion from a seated position. The combination of the data from multiple sensors resulted in R2 coefficient values of 0.88 or higher. This preliminary work demonstrates the feasibility of the presented system. Future work should include more participants to further assess the accuracy and repeatability in the presence of larger interpersonal variability. [ABSTRACT FROM AUTHOR]

Many researchers have postulated inexpensive methods to estimate respiratory volumes from respirationinduced movements of the upper body. In the development of smart garments, the number and the optimal positioning of sensors is an essential aspect. Therefore, the symmetry of upper body respiratory movements was investigated based on the measurement data from a motion capture system. In the ventral central area, coefficients of determination above 0.99 regarding movements of symmetrical markers mean that sensors can be placed without restrictions in the position mirrored on the sagittal plane. This simplifies sensor positioning in a smart shirt and expands the range of applications of smart shirts for respiratory monitoring.

Wearable 2.0 research has been conducted on the manufacture of smart fitness wear that collects bio-signals through the wearing of a textile-based electrode. Among them, the electromyography (EMG) suit measures the electrical signals generated by the muscles to check their activity, such as contraction and relaxation. General gel-type electrodes have been reported to cause skin diseases due to an uncomfortable feel and skin irritation when attached to the skin for a long time. Dry electrodes of various materials are being developed to solve this problem. Previous research has reported EMG detectio performance and conducted economic comparisons according to the size and shape of the embroidery electrode. On the other hand, these embroidery electrodes still have foreign body sensations. In this study, a moss sEMG electrode was produced with various shapes (W3 and WF) and loop lengths (1–5 mm). The optimized conditions of the embroidery-based electrodes were derived and analyzed with the tactile comfort factors and sensing performances. As the loop length of the electrode increased, MIU and Qmax increased, but the SMD decreased due to the free movement of the threads constituting the loop. Impedance and sEMG detection performance showed different trends depending on the electrode type. [ABSTRACT FROM AUTHOR]

Textile clothing is closely intertwined with human daily life, and the fiber materials used in it have undergone significant changes with the advancement of science and technology. Smart fibers have emerged within this context. Smart fibers refer to fibers with ability to sense changes in the external environment or internal conditions and respond accordingly. They possess not only the physical properties of traditional fiber materials such as softness, lightness, and durability but also interactive functions like perception, response, and interaction. As a result, they have garnered significant attention. Applying smart fibers to clothing can enable real-time monitoring of body parameters, environmental conditions, and exercise status, providing users with valuable information. This has immense value in fields such as healthcare, sports training, and improving quality of life. Therefore, we comprehensively analyze and interpret current research literature on the materials, functions, and technologies of smart fibers, aiming to provide quantitative research data to support the development and application pathways in the field of smart fibers.To elucidate the current research status in the domain of smart fibers concerning materials, functions, and technologies, we utilized CiteSpace software for searches in the databases of China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) . We employed search terms like “intelligent fiber”, “intelligent material”, “intelligent technology”, “intelligent application”, “textile/fiber intelligent/smart”, “intelligent/smart material”, “intelligent/smart technology”, and “intelligent/smart application”, resulting in a total of 3 671 documents. Visual graph analysis, incorporating multidimensional data such as document age distribution, research institutions, research authors, keywords, keyword clustering, and burst terms, was conducted to form a literature review of research related to smart fibers. This study leverages the software’s features, including keyword extraction, co-citation analysis, and co-occurrence analysis. On the one hand, quantitative bibliometric methods were employed to generate information such as document count, country distribution, and highly cited authors in smart fiber research. We also analyzed the co-occurrence of research authors and institutions, keyword co-occurrence, clustering, and burst term graphs to uncover research hotspots. On the other hand, qualitative manual interpretation methods were employed for an in-depth examination of subject information and keyword clusters based on data maps. This helped in classification and correcting the bias of quantitative analysis, enabling a critical qualitative analysis of clustering topics to reveal the current research status in the field of smart fibers, thus forming a literature review on research related to smart fibers.Through an analysis of the main research authors and institutions, it is found that there is a certain level of collaboration among research authors in Chinese literature, as well as among research institutions. However, the collaboration among various research authors and among various research institutions in English literature is even more closely knit. Through keyword clustering research, it becomes evident that current smart fiber research predominantly centers around the fields of engineering and science. This indicates that current research in smart fibers is more concentrated in the domain of materials and technology, with discussions on practical applications still in the early stages. The research areas covered in Chinese literature predominantly focus on #1 intelligence, #2 composite materials, #3 phase change materials, #4 textile industry, and #5 bionics. In contrast, English literature emphasizes #1 wearable electronics, #2 smart materials, #3 smart clothing, #4 smart textile, and #5 electrical conductivity. From the perspective of Burst Term analysis, future research hotspots in smart fibers will primarily revolve around areas like smart clothing, health monitoring, and conductive sensing. Additionally, there will be a focus on the information that smart fiber products can provide when connected to the Internet of Things, maximizing their utility. The research findings regarding the intelligent properties of smart fibers will serve as valuable reference suggestions for future research and development in the field of smart fibers. [ABSTRACT FROM AUTHOR]

In many smart textile development studies, sensors and electro-conductive yarns have been widely investigated and used as essential components, especially in the fields of medicine, sport, work wear, and special applications. Wearable sensors provide a means to monitor the wearer's health through physiological measurements in a natural setting or are used to detect potential hazards and alert users and/or caretakers. The aim of the research is to develop a prototype of wearable electronics that consists of high-performance clothing with an integrated energy harvesting system for converting the mechanical energy of human movements into electrical energy. Within the framework of the research, a system for determining human physiological and/or environmental parameters and transmitting data was developed and integrated into clothing modified with sol–gel technology for indoor and outdoor use. Although the created flat inductive elements of the energy harvesting system retain their performance during the hydrothermal treatment process, at the same time, the other elements of the smart clothing system (especially electro-conductive yarns) rapidly lose their electrical conductivity. The modified knitwear provided a longer time between washing cycles to protect the embedded wearable electronics, and the impact of surface modification with sol–gel on wearing comfort was evaluated. [ABSTRACT FROM AUTHOR]

The measurement of respiratory volume based on upper body movements by means of a smart shirt is increasingly requested in medical applications. This research used upper body surface motions obtained by a motion capture system, and two regression methods to determine the optimal selection and placement of sensors on a smart shirt to recover respiratory parameters from benchmark spirometry values. The results of the two regression methods (Ridge regression and the least absolute shrinkage and selection operator (Lasso)) were compared. This work shows that the Lasso method offers advantages compared to the Ridge regression, as it provides sparse solutions and is more robust to outliers. However, both methods can be used in this application since they lead to a similar sensor subset with lower computational demand (from exponential effort for full exhaustive search down to the order of O (n2)). A smart shirt for respiratory volume estimation could replace spirometry in some cases and would allow for a more convenient measurement of respiratory parameters in home care or hospital settings. [ABSTRACT FROM AUTHOR]

Abstract Participation and social inclusion influence individuals’ health and well-being. These factors can be easily disturbed, especially for those with disabilities. Designers and engineers have tried harnessing technology to assist people via producing prototypes of assistive devices, such as smart clothing and furniture. This study approaches that user surface and inspects the user’s needs for participation through clothing and furniture. We thus arranged two similar workshops with student participants (n = 37) from four different educational units, creating 10 innovative concepts to support participation and social inclusion. All aimed to support participation via improved self-regulation, increased safety, or environmental control. Most of the concepts were connectible to another device, such as a mobile phone. All devices were made adjustable to meet personal preferences. This study aligns with previous ones by concluding that assistive technology should be unobtrusive, give timely responses, and interact with other devices. These initial concepts are ready to be turned into tangible prototypes. Article highlights Participation and social inclusion have remarkable meaning for an individual’s well-being and health. Commonly, assistive technology aims to solve challenges in daily living by promoting health and well-being. For this reason, we arranged two similar co-creation workshops and asked the participants to innovate smart clothing and furniture concepts that will promote greater participation and more social inclusion. This study also identified users’ needs, such as increased safety and independence, supported communication, self-regulation and awareness, and an effective learning tool. The majority of the concepts were designed to be adjustable to meet personal preferences, let individuals interact with other devices (such as a mobile phone), and give timely responses.

Ferroelectrets, featuring strong piezoelectric activity, flexibility, lightweight, and low cost, are advanced material and have attractive prospects for various sensors and actuators. However, large‐scale production of ferroelectret‐based devices and their straightforward implementation in complicated structures remain difficult tasks. In this study, a novel self‐shielding threadlike piezoelectric pressure sensor based on irradiation cross‐linked polypropylene (IXPP) ferroelectrets with a symmetric coaxial structure, named Ferroelectret Coaxial Sensor (FCS), is designed, prepared, and characterized. Besides, such sensors with a length of up to 300 m are successfully produced by an industrial continuous production line, confirming that the fabrication procedure is compatible with it and that the FCS can be mass‐produced in the future. The results show that the hydrostatic piezoelectric coefficient up to 55 pC/N is achieved in the FCS, which is around four times of magnitude higher than those of commercially available piezo‐cables made of poly (vinylidene fluoride). Smart carpets and wristers weaved with an integrated FCS, that can be produced by an industrial production line, are sensitive, flexible/stretchable, washable, and breathable, demonstrating great potential in motion recognition for health care. A laboratory prototype of traffic sensors based on the FCS indicates its capability in speed meauring and dynamic weighing for vehicles. This study will greatly promote applications of ferroelectrets in wearable devices, smart housing, intelligent transportation, etc. [ABSTRACT FROM AUTHOR]

Thermoelectric (TE) technology is promising for reducing thermal discomfort of workers during their routine professional activities. In this manuscript, a preliminary evaluation of a newly developed personal cooling system (PCS) with flexible TE modules is presented based on an analysis of cooling efficiency and power consumption. For this purpose, tests with human participation were performed involving the monitoring of local skin temperature changes and electrical parameters of the controller. Thanks to TE cooling, a significant reduction of local skin temperature was observed at the beginning of the experiment, reaching as much as 6 °C. However, the observed effect systematically became weaker with time, with the temperature difference decreasing to about 3 °C. Cooling efficiency stayed at the same level over the ambient temperature range from 25 °C to 35 °C. The obtained results showed that a proper fitting of the PCS to the human body is a crucial factor influencing the PCS cooling efficiency. [ABSTRACT FROM AUTHOR]

Tiffeneau manoeuvres are an important method in pulmonary function testing of the human lungs and can help to diagnose respiratory obstructions. Data from a motion capture system and a spirometer was used to evaluate Tiffeneau indexes which can theoretically be derived via a Smart-Shirt that incorporates three circumference measurements of the upper body. The mean error was 4.5% regarding the Tiffeneau indexes gained by the spirometer, indicating that clinical diagnosis of obstruction is potentially possible using a Smart-Shirt.

Pressure injuries (PIs) are a major public health problem and can be used as quality-of-care indicators. An incipient development in the field of medical devices takes the form of Smart Health Textiles, which can possess innovative properties such as thermoregulation, sensing, and antibacterial control. This protocol aims to describe the process for the development of a new type of smart clothing for individuals with reduced mobility and/or who are bedridden in order to prevent PIs. This paper's main purpose is to present the eight phases of the project, each consisting of tasks in specific phases: (i) product and process requirements and specifications; (ii and iii) study of the fibrous structure technology, textiles, and design; (iv and v) investigation of the sensor technology with respect to pressure, temperature, humidity, and bioactive properties; (vi and vii) production layout and adaptations in the manufacturing process; (viii) clinical trial. This project will introduce a new structural system and design for smart clothing to prevent PIs. New materials and architectures will be studied that provide better pressure relief, thermo-physiological control of the cutaneous microclimate, and personalisation of care. [ABSTRACT FROM AUTHOR]

Wearables have been applied in the field of fitness in recent years to monitor human muscles by recording electromyographic (EMG) signals. Understanding muscle activation during exercise routines allows strength athletes to achieve the best results. Hydrogels, which are widely used as wet electrodes in the fitness field, are not an option for wearable devices due to their characteristics of being disposable and skin-adhesion. Therefore, a lot of research has been conducted on the development of dry electrodes that can replace hydrogels. In this study, to make it wearable, neoprene was impregnated with high-purity SWCNTs to develop a dry electrode with less noise than hydrogel. Due to the impact of COVID-19, the demand for workouts to improve muscle strength, such as home gyms and personal trainers (PT), has increased. Although there are many studies related to aerobic exercise, there is a lack of wearable devices that can assist in improving muscle strength. This pilot study proposed the development of a wearable device in the form of an arm sleeve that can monitor muscle activity by recording EMG signals of the arm using nine textile-based sensors. In addition, some machine learning models were used to classify three arm target movements such as wrist curl, biceps curl, and dumbbell kickback from the EMG signals recorded by fiber-based sensors. The results obtained show that the EMG signal recorded by the proposed electrode contains less noise compared to that collected by the wet electrode. This was also evidenced by the high accuracy of the classification model used to classify the three arms workouts. This work classification device is an essential step towards wearable devices that can replace next-generation PT. [ABSTRACT FROM AUTHOR]

Premature birth is considered to be a substantial problem in perinatal medicine, which in the vast majority of cases (>60%), concerns African and South Asian countries. Nevertheless, prematurity is a global problem and is faced by both less-developed (where 12% of babies are prematurely born) and well-developed countries (with 9% prematurity rate) [1, 2]. The percentage of children born prematurely, i.e., before the 37th week of pregnancy, was 8.7% in Europe, while, in Poland, it was 7.34% [3]. Care of prematurely born babies is a huge challenge for parents and medical staff in the neonatal intensive care unit. Preterm infants, because of their low weight and gestational age, are prone to health problems and even death. For this reason, continuous monitoring of health parameters plays an important role. It is achieved by the use of various sensors that are inserted in infants' garments. Sensor systems monitor an infant's health condition, and then the data are transmitted to doctors or parents. This article is for illustrative purposes, aimed at presenting solutions such as the use of sensors for monitoring infants' physiological parameters. [ABSTRACT FROM AUTHOR]

Intense physical activity and high ambient temperature cause construction workers to be exposed to an increased risk of overheating, especially in the summer season. Personal cooling systems have great potential to support workers’ thermoregulation and reduce this risk. In particular, solutions based on the thermoelectric effect can provide high cooling effectiveness and ergonomics at the same time. In this paper, a newly developed active clothing solution with flexible thermoelectric modules intended for outdoor activities is presented. The active clothing was subjected to utility tests on a treadmill under laboratory conditions with the participation of potential end users. A comparison of results from cooled and uncooled places indicated a reduction in local skin temperature of as much as 2.7 °C. Moreover, a gradual decrease in temperature in the uncooled place during the experiment was observed. Based on the positive results from this evaluation, the personal cooling system was integrated into active clothing within the ASSIST-IoT NGIoT reference architecture. This allows contextual and personalized adjustment of the cooling power to be provided using AI techniques and, additionally, by using data from a weather station and a smartwatch. Training procedures and models for the AI system are proposed, with special attention paid to the privacy aspect.

Monitoring human movement is highly relevant in mobile health applications. Textile-based wearable solutions have the potential for continuous and unobtrusive monitoring. The precise estimation of joint angles is important in applications such as the prevention of osteoarthritis or in the assessment of the progress of physical rehabilitation. We propose a textile-based wearable device for knee angle estimation through capacitive sensors placed in different locations above the knee and in contact with the skin. We exploited this modality to enhance the baseline value of the capacitive sensors, hence facilitating readout. Moreover, the sensors are fabricated with only one layer of conductive fabric, which facilitates the design and realization of the wearable device. We observed the capability of our system to predict knee sagittal angle in comparison to gold-standard optical motion capture during knee flexion from a seated position and squats: the results showed an R2 coefficient between 0.77 and 0.99, root mean squared errors between 4.15 and 12.19 degrees, and mean absolute errors between 3.28 and 10.34 degrees. Squat movements generally yielded more accurate predictions than knee flexion from a seated position. The combination of the data from multiple sensors resulted in R2 coefficient values of 0.88 or higher. This preliminary work demonstrates the feasibility of the presented system. Future work should include more participants to further assess the accuracy and repeatability in the presence of larger interpersonal variability.

Measurement of accurate tidal volumes based on respiration-induced surface movements of the upper body would be valuable in clinical and sports monitoring applications, but most current methods lack the precision, ease of use, or cost effectiveness required for wide-scale uptake. In this paper, the theoretical ability of different sensors, such as inertial measurement units, strain gauges, or circumference measurement devices to determine tidal volumes were investigated, scrutinised and evaluated. Sixteen subjects performed different breathing patterns of different tidal volumes, while using a motion capture system to record surface motions and a spirometer as a reference to obtain tidal volumes. Subsequently, the motion-capture data were used to determine upper-body circumferences, tilt angles, distance changes, movements and accelerations—such data could potentially be measured using optical encoders, inertial measurement units, or strain gauges. From these parameters, the measurement range and correlation with the volume signal of the spirometer were determined. The highest correlations were found between the spirometer volume and upper body circumferences; surface deflection was also well correlated, while accelerations carried minor respiratory information. The ranges of thorax motion parameters measurable with common sensors and the values and correlations to respiratory volume are presented. This article thus provides a novel tool for sensor selection for a smart shirt analysis of respiration. [ABSTRACT FROM AUTHOR]

Wearable technologies are making a significant impact on people’s way of living thanks to the advancements in mobile communication, internet of things (IoT), big data and artificial intelligence. Conventional wearable technologies present many challenges for the continuous monitoring of human health conditions due to their lack of flexibility and bulkiness in size. Recent development in e-textiles and the smart integration of miniature electronic devices into textiles have led to the emergence of smart clothing systems for remote health monitoring. A novel comprehensive framework of smart clothing systems for health monitoring is proposed in this paper. This framework provides design specifications, suitable sensors and textile materials for smart clothing (e.g., leggings) development. In addition, the proposed framework identifies techniques for empowering the seamless integration of sensors into textiles and suggests a development strategy for health diagnosis and prognosis through data collection, data processing and decision making. The conceptual technical specification of smart clothing is also formulated and presented. The detailed development of this framework is presented in this paper with selected examples. The key challenges in popularizing smart clothing and opportunities of future development in diverse application areas such as healthcare, sports and athletics and fashion are discussed.

Flexible wearable strain sensors are becoming increasingly popular due to their ability to monitor physiological signals and to detect motion in a wide range of applications. However, the development of strain sensors with high sensitivity and wide sensing range remains a challenge. Herein, a film-nanowire double sensoring layer structure (FNDLS) crack strain sensor with high sensitivity, wide strain range and fast response is proposed. The FNDLS with hierarchical synergistic are integrated onto fabrics using a heat pressing process. The FNDLS has a very low initial resistance and a high density of channel cracks to have the high sensitivity of the strain sensor and to extend the strain range of the strain sensor through the synergistic bridging effect of the AgNWs. Due to this structure, the sensitivity of the sensor can reach 70945 , the strain range can reach about 40 %, and response time is less than 129 ms. Furthermore, the sensor demonstrates exceptional cycling stability and favourable frequency characteristics. Its superior performance makes it suitable for monitoring pulse waves and detecting motion through smart clothing. [Display omitted] • Strain sensors with a double conductive layer based on heat pressing method. • Strain sensors has ultra-high sensitivity, wide strain range and fast response. • Sensor can be used for pulse wave monitoring and fitness motion correction. [ABSTRACT FROM AUTHOR]

In recent years, flexible, easy-to-fabricate, and low-cost electronic skins (E-skins) have attracted considerable attention, due to their enormous demand in wearable device applications. Based on a carbon nanotube (CNT)/nonwoven fabric, three types of E-skins were fabricated using a low-cost and scalable approach, and detected various signals, like pressure, stretch, flexion, temperature, and humidity. Due to the wrinkled and porous microstructure of CNT/nonwoven fabric, the pressure-sensitive E-skin demonstrates a high gauge factor (GF) value of 19.12 kPa-1 and 5.38 kPa-1 with a pressure range of 15–6125 Pa and 6125–12005 Pa, respectively. Unlike traditional paper-based E-skins, the stretch/flexion/temperature-sensitive E-skin could detect the stretch strain, and its GF values were 3.81, 0.51 rad-1, and 1.4×10-3 ℃-1 for the detection of stretch, flexion and temperature. For the humidity-sensitive E-skin, its GF value was calculated to be 2.8×10-2 and 0.20 with the relative humidity range of 55–75% and 75–95%. The favorable performance of the E-skins allows their integration into smart clothing, where they successfully monitored human motion, physiological and external environmental signals in real time. Furthermore, the prepared E-skins have also been integrated into an electronic glove, where they simultaneously detected the bending and pressure signals of human fingers, demonstrating application potential in the field of telediagnosis. [Display omitted] • Compared with other E-skins having the similar thickness, our E-skins had much higher sensitivity toward pressure. • Based on the CNT/nonwoven fabric, the E-skins could detect more types of signals, compared with other E-skins. • Our E-glove had the ability to detect the bending and pressure signals of human fingers at the same time. [ABSTRACT FROM AUTHOR]

Wearable 2.0 research has been conducted on the manufacture of smart fitness wear that collects bio-signals through the wearing of a textile-based electrode. Among them, the electromyography (EMG) suit measures the electrical signals generated by the muscles to check their activity, such as contraction and relaxation. General gel-type electrodes have been reported to cause skin diseases due to an uncomfortable feel and skin irritation when attached to the skin for a long time. Dry electrodes of various materials are being developed to solve this problem. Previous research has reported EMG detectio performance and conducted economic comparisons according to the size and shape of the embroidery electrode. On the other hand, these embroidery electrodes still have foreign body sensations. In this study, a moss sEMG electrode was produced with various shapes (W3 and WF) and loop lengths (1–5 mm). The optimized conditions of the embroidery-based electrodes were derived and analyzed with the tactile comfort factors and sensing performances. As the loop length of the electrode increased, MIU and Qmax increased, but the SMD decreased due to the free movement of the threads constituting the loop. Impedance and sEMG detection performance showed different trends depending on the electrode type.

The detection of biosignals by using a comfortable material is important to improve human health. This paper presents a complete wearable system with smart clothing for the long-term monitoring of lead-I ECG and respiratory signals. The proposed system is divided into three parts, including biosignal-monitoring clothing, a biosignal acquisition device, and a software platform. The smart clothing integrates fabric-based ECG dry electrodes, conductive fiber traces, and a high-sensitivity capacitive respiration transducer to sense the biosignals. The challenge including the integration of ECG electrodes and the respiration transducer in the clothing system to provide the high-quality ECG and respiration signals for clinical use has been overcome in the proposed biosignal-monitoring clothing. The sensed signals on the smart clothing are collected in the biosignal-acquisition device through fabric-based traces and a specially designed clothing structure. Furthermore, the biosignals are processed using the biosignal-acquisition device and sent to the remote smart device through the Bluetooth module. The device according to the requirement of the front-end clothing system and the actual measurement accuracy is implemented and contributed onto the reduction in the effect of motion artifact. The software platform on the smart device provides real-time biosignal monitoring and health-information analysis. A highly efficient ECG QRS complex detection algorithm and respiratory-rate detection algorithm are also proposed. The ECG QRS complex detection algorithm is verified using the MIT/BIH Arrhythmia Database to demonstrate the achievement of high performance. The overall measured sensitivity, positive prediction, and error rate of the proposed algorithm are 99.86%, 99.93%, and 0.19%, respectively. The measured ECG signal of the clothing system is compared with the commercial silver/silver-chloride electrode by using the BIOPAC MP36 acquisition system. The result confirms the high quality of the signal, so the measured ECG signal can be used for medical applications. The function of the respiration transducer is verified by the BIOPAC SS11LA airflow transducer, and the overall accuracy of 19 test subjects is 98.74%. Using the proposed system, long-term health care in daily life can be achieved.

Abstract Nowadays, the need for protective devices at man–machine interfaces is increasing in the fields of traffic, sports, construction, and military, etc. Dynamic pressure sensing technology with wide measuring range, high sensitivity, softness, and fast response is crucial for evaluation and optimization of the personal protective equipment under impact scenarios. However, current sensors hardly possess all the aforesaid required characteristics. For the first time, this article reports the evaluation and application of an innovative soft pressure sensor with modulus of 2 MPa, maximum pressure of 8 MPa, and over 500‐Hz frequency. A theoretical model, taking strain rate into consideration, is established to characterize the dynamic sensing behavior. A sensing network in the form of smart clothing is developed and used in a sled crash test, which is a standard approach to evaluate the safety of automobiles in collisions. The pressure distribution over the dummy's surface during the crash is acquired in real‐time, and compared with numerical simulations. This study is important to the study of occupant injury and crashworthiness design for vehicles, and it will benefit the automotive industry. With the built‐in sensing network, the smart clothing has promising applications in the pressure mapping of 3D flexible man–machine interface under impact scenarios.

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The article presents simple modeling and experimental verification of the power required for thermal comfort in electrically heated clothing. The clothing consists of a jumpsuit with embedded heating insets, controlled by a dedicated microprocessor system. The user is able to set heating power using a smartphone app. The experiments, conducted in a mobile freezing chamber, aimed at verification of the model of theoretical power (according to ISO 11079) required to maintain thermal comfort in ambient temperatures below 0 °C. Three participants were asked to adjust heating power to reach thermal comfort. The experiment revealed the required power to be only 40–60% of the theoretical one, meaning that the design of the electrically heating clothing relying solely on the theoretical models and standards would lead to oversizing of the heating system power. Further study indicated that the mean skin temperature by itself is not sufficient as an input to the algorithm for automatic maintaining of thermal comfort, even in stationary conditions. [ABSTRACT FROM AUTHOR]

In current society, smart clothing technology has become a critical way to improve the life quality of the elderly. This work conducted a category product evaluation and user demand system through the bibliometrics method, product evaluation analysis, focus group interviews and questionnaires. Based on the system, we designed smart clothing from the aspects of the clothing structure, hardware, software program and intelligent terminal platform to meet the needs of disabled elderly people and their caregivers in multiple scenarios. According to the test results of the smart clothing, the average error of temperature and humidity monitoring is 0.20° and 2.88%RH. The time of putting on-taking off clothing in 6 representative daily scenarios was reduced by 51.67%. The daily body checking times, uncomfortable behaviours, and the anxiety of caregivers was decreased by 42.31%, 28.52% and 74.37%. Compared with ordinary clothing, six of the eight comfort performances are basically the same, and two are slightly worse. [ABSTRACT FROM AUTHOR]

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Copyright of Wool Textile Journal is the property of National Wool Textile Science & Technology Information Center and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)