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Wearable strain sensors play a pivotal role in real-time human motion detection and health monitoring. Traditional fabric-based strain sensors, typically with a positive Poisson's ratio, face challenges in maintaining sensitivity and comfort during human motion due to conflicting resistance changes in different strain directions. In this work, high-performance stretchable strain sensors are developed based on graphene-modified auxetic fabrics (GMAF) for human motion detection in smart wearable devices. The proposed GMAF sensors, with a negative Poisson's ratio achieved through commercially available warp-knitting technology, exhibit an 8-fold improvement in sensitivity compared to conventional plain fabric sensors. The unique auxetic fabric structure enhances sensitivity by synchronizing resistance changes in both wale and course directions. The GMAF sensors demonstrate excellent washability, showing only slight degradation in auxeticity and an acceptable increase in resistance after 10 standard wash cycles. The GMAF sensors maintain stability under different strain levels and various motion frequencies, emphasizing their dynamic performance. The sensors exhibit superior conformability to joint movements, which effectively monitor a full range of motions, including joint bending, sports activities, and subtle actions like coughing and swallowing. The research underscores a promising approach to achieve industrial-scale production of wearable sensors with improved performance and comfort through fabric structure design.

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Textile-based surface electromyography (sEMG) electrodes have emerged as a prominent tool in muscle fatigue assessment, marking a significant shift toward innovative, noninvasive methods. This review examines the transition from metallic fibers to novel conductive polymers, elastomers, and advanced material-based electrodes, reflecting on the rapid evolution of materials in sEMG sensor technology. It highlights the pivotal role of materials science in enhancing sensor adaptability, signal accuracy, and longevity, crucial for practical applications in health monitoring, while examining the balance of clinical precision with user comfort. Additionally, it maps the global sEMG research landscape of diverse regional contributors and their impact on technological progress, focusing on the integration of Eastern manufacturing prowess with Western technological innovations and exploring both the opportunities and challenges in this global synergy. The integration of such textile-based sEMG innovations with artificial intelligence, nanotechnology, energy harvesting, and IoT connectivity is also anticipated as future prospects. Such advancements are poised to revolutionize personalized preventive healthcare. As the exploration of textile-based sEMG electrodes continues, the transformative potential not only promises to revolutionize integrated wellness and preventive healthcare but also signifies a seamless transition from laboratory innovations to real-world applications in sports medicine, envisioning the future of truly wearable material technologies.

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Laser safety is starting to play an increasingly important role, especially when the laser is used as a tool. Passive laser safety systems quickly reach their limits and, in some cases, provide inadequate protection. To counteract this, various active systems have been developed. Flexible and especially textile-protective materials pose a special challenge. The market still lacks personal protective equipment (PPE) for active laser safety. Covering these materials with solar cells as large-area optical detectors offers a promising possibility. In this work, an active laser protection fabric with amorphous silicon solar cells is presented as a large-scale sensor for continuous wave and pulsed lasers (down to ns). First, the fabric and the solar cells were examined separately for irradiation behavior and damage. Laser irradiation was performed at wavelengths of 245, 355, 532, and 808 nm. The solar cell sensors were then applied directly to the laser protection fabric. The damage and destruction behavior of the active laser protection system was investigated. The results show that the basic safety function of the solar cell is still preserved when the locally damaged or destroyed area is irradiated again. A simple automatic shutdown system was used to demonstrate active laser protection within 50 ms.

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The increasing interest in karate has also attracted the attention of researchers, especially in combining the equipment used by practitioners with technology to prevent injuries, improve technical skills and provide appropriate scoring. Contrary to the sport of taekwondo, the development of a smart body protector in the sport of karate is still a niche field to be researched. This study focused on developing piezoresistive, textile-based pressure sensors using piezoresistive film, conductive fabric as well as different bonding materials and methods. Primarily, small-scale sensors were produced using ultrasonic welding, hot press welding and oven curing. These were characterized using a universal testing machine and specific conditioning and data-acquisition hardware combined with custom processing software. Large-scale sensors were then manufactured to be placed inside the karate body protector and characterized using cyclic testing. The conditioning circuit allows flexible gain adjustment, and it was possible to obtain a stable signal with an output of up to 0.03 V/N, an adequate signal for the tested force range. The transfer function shows some drift over the cycles, in addition to the expected hysteresis and slight nonlinearity, which can be compensated for. Finally, the configuration with the best results was tested in real practice tests; during these tests the body protector was placed on a dummy as well as on a person. The results showed that the piezoresistive textile-based pressure sensor produced is able to detect and quantify the impact of even light punches, providing an unobtrusive means for performance monitoring and score calculation for competitive practice of this sport.

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As the focus on physical health increases, the market demand for flexible wearable sensors increases. Textiles combined with sensitive materials and electronic circuits can form flexible, breathable high-performance sensors for physiological-signal monitoring. Carbon-based materials such as graphene, carbon nanotubes (CNTs), and carbon black (CB) have been widely utilized in the development of flexible wearable sensors due to their high electrical conductivity, low toxicity, low mass density, and easy functionalization. This review provides an overview of recent advancements in carbon-based flexible textile sensors, highlighting the development, properties, and applications of graphene, CNTs, and CB for flexible textile sensors. The physiological signals that can be monitored by carbon-based textile sensors include electrocardiogram (ECG), human body movement, pulse and respiration, body temperature, and tactile perception. We categorize and describe carbon-based textile sensors based on the physiological signals they monitor. Finally, we discuss the current challenges associated with carbon-based textile sensors and explore the future direction of textile sensors for monitoring physiological signals.

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(1) Background: In alpine skiing, senior athletes and especially women have a high risk of knee injury. This may also be related to muscular fatigue (MF) of the knee-stabilizing thigh muscles. This study investigates both the evolution of muscle activity (MA) and of MF of the thighs throughout an entire skiing day. (2) Methods: n = 38 female recreational skiers over 40 years of age performed four specific skiing tasks (plough turns, V-steps uphill, turns with short, and middle radii) at specific times, while freely skiing the rest of the day. Surface EMG of the thigh muscle groups (quadriceps and hamstrings) was measured using special wearables (EMG pants). Apart from standard muscle activity parameters, the EMG data were also processed in the frequency domain to calculate the mean frequency and its shift over the day as a metric of muscle fatigue. (3) Results: The EMG pants showed reliable signal quality over the entire day, with BMI not impacting this. MF increased during skiing before and for both muscle groups significantly (p < 0.006) during lunch. MF, however, was not reflected in the quadriceps-hamstrings ratio. The plough manoeuvre seems to require significantly (p < 0.003) more muscle dynamics than the three other tasks. (4) Conclusion: MF may be quantified over an entire skiing day and thus fatigue information could be given to the skier. This is of major importance for skiers at the beginner level dominantly performing plough turns. Crucial for all skiers: There is no regenerative effect of a 45-min lunch break.

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Personal protective equipment (PPE) is an essential key factor in standardizing safety within the workplace. Harsh working environments with long working hours can cause stress on the human body that may lead to musculoskeletal disorder (MSD). MSD refers to injuries that impact the muscles, nerves, joints, and many other human body areas. Most work-related MSD results from hazardous manual tasks involving repetitive, sustained force, or repetitive movements in awkward postures. This paper presents collaborative research from the School of Electrical Engineering and School of Allied Health at Curtin University. The main objective was to develop a framework for posture correction exercises for workers in hostile environments, utilizing inertial measurement units (IMU). The developed system uses IMUs to record the head, back, and pelvis movements of a healthy participant without MSD and determine the range of motion of each joint. A simulation was developed to analyze the participant's posture to determine whether the posture present would pose an increased risk of MSD with limits to a range of movement set based on the literature. When compared to measurements made by a goniometer, the body movement recorded 94% accuracy and the wrist movement recorded 96% accuracy.

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Knowledge of foot growth can provide information on the occurrence of children's growth spurts and an indication of the time to buy new shoes. Podiatrists still do not have enough evidence as to whether footwear influences the structural development of the feet and associated locomotor behaviours. Parents are only willing to buy an inexpensive brand, because children's shoes are deemed expendable due to their rapid foot growth. Consumers are not fully aware of footwear literacy; thus, views of consumers on children's shoes are left unchallenged. This study aims to embed knitted smart textile sensors in children's shoes to sense the growth and development of a child's feet-specifically foot length. Two prototype configurations were evaluated on 30 children, who each inserted their feet for ten seconds inside the instrumented shoes. Capacitance readings were related to the proximity of their toes to the sensor and validated against foot length and shoe size. A linear regression model of capacitance readings and foot length was developed. This regression model was found to be statistically significant (p-value = 0.01, standard error = 0.08). Results of this study indicate that knitted textile sensors can be implemented inside shoes to get a comprehensive understanding of foot development in children.

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The need for more efficient health services and the trend of a healthy lifestyle pushes the development of smart textiles. Since textiles have always been an object of everyday life, smart textiles promise an extensive user acceptance. Thereby, the manufacture of electrical components based on textile materials is of great interest for applications as biosensors. Organic electrochemical transistors (OECTs) are often used as biosensors for the detection of saline content, adrenaline, glucose, etc., in diverse body fluids. Textile-based OECTs are mostly prepared by combining a liquid electrolyte solution with two separate electro-active yarns that must be precisely arranged in a textile structure. Herein, on the other hand, a biosensor based on a textile single-component organic electrochemical transistor with a hardened electrolyte was developed by common textile technologies such as impregnation and laminating. Its working principle was demonstrated by showing that the herein-produced transistor functions similarly to a switch or an amplifier and that it is able to detect ionic analytes of a saline solution. These findings support the idea of using this new device layout of textile-based OECTs as biosensors in near-body applications, though future work must be carried out to ensure reproducibility and selectivity, and to achieve an increased level of textile integration.

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One of the main challenges during the integration of a carbon/polymer-based nanocomposite sensor on textile substrates is the fabrication of a homogeneous surface of the nanocomposite-based thin films, which play a major role in the reproducibility of the sensor. Characterizations are therefore required in every fabrication step to control the quality of the material preparation, deposition, and curing. As a result, microcharacterization methods are more suitable for laboratory investigations, and electrical methods can be easily implemented for in situ characterization within the manufacturing process. In this paper, several textile-based pressure sensors are fabricated at an optimized concentration of 0.3 wt.% of multiwalledcarbon nanotubes (MWCNTs) composite material in PDMS. We propose to use impedance spectroscopy for the characterization of both of the resistive behavior and capacitive behavior of the sensor at several frequencies and under different loads from 50 g to 500 g. The impedance spectra are fitted to a model composed of a resistance in series with a parallel combination of resistance and a constant phase element (CPE). The results show that the printing parameters strongly influence the impedance behavior under different loads. The deviation of the model parameter α of the CPE from the value 1 is strongly dependent on the nonhomogeneity of the sensor. Based on an impedance spectrum measurement followed by parameter extraction, the parameter α can be determined to realize a novel method for homogeneity characterization and in-line quality control of textile-integrated wearable sensors during the manufacturing process.

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Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact HR/RR measurement remains a challenge due to imprecise readings. "Invisible" wearables integrated into day-to-day garments have the potential to produce precise readings with a comfortable user experience. Sleep studies and patient monitoring benefit from "Invisibles" due to longer wearability without significant discomfort. This paper suggests a novel method to reduce the footprint of sleep monitoring devices. We use a single silver-coated nylon fabric band integrated into a substrate of a standard cotton/nylon garment as a resistive elastomer sensor to measure air and blood volume change across the chest. We introduce a novel event-based architecture to process data at the edge device and describe two algorithms to calculate real-time HR/RR on ARM Cortex-M3 and Cortex-M4F microcontrollers. RR estimations show a sensitivity of 99.03% and a precision of 99.03% for identifying individual respiratory peaks. The two algorithms used for HR calculation show a mean absolute error of 0.81 ± 0.97 and 0.86±0.61 beats/min compared with a gold standard ECG-based HR. The event-based algorithm converts the respiratory/pulse waveform into instantaneous events, therefore reducing the data size by 40-140 times and requiring 33% less power to process and transfer data. Furthermore, we show that events hold enough information to reconstruct the original waveform, retaining pulse and respiratory activity. We suggest fabric sensors and event-based algorithms would drastically reduce the device footprint and increase the performance for HR/RR estimations during sleep studies, providing a better user experience.

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The development of wearable devices has stimulated significant engineering and technologies of textile electronics (TEs). Improving sensing, energy-storing, and electro-heating capabilities of TEs is still challenging but crucial for their practical applications. Herein, a drip-coating method that constructs a dense ß-FeOOH scaffold on a nylon strip for enhancing polypyrrole loading is proposed, which facilitates the fabrication of highly conductive and hydrophobic PFCNS (polypyrrole/ß-FeOOH/nylon strip). The space provided by the ß-FeOOH scaffold increases the mass of polypyrrole on fibers from 1.1 (polypyrrole/nylon strip) to 3.0 mg cm-2 (polypyrrole/ß-FeOOH/nylon strip), which decreases the resistance from 104.96 to 34.29 Ω cm-1. The PFCNS exhibits a linear elastic modulus of 0.758 MPa within 150% strain, performs a unique resistance variation mechanism, and enables great sensing capability with rapid response time (140 ms), long durability (10,000 stretching-recovering), and effective movement monitoring (e.g., breathing, back bending, jumping). The sensing signals for knee bending have been analyzed in detail by combining with both stretching and pressing response mechanisms. The PFCNS electrode attains a diffusion-controlled capacitance of 574 mF cm-2 and discharging-capacitance of 916 mF cm-2. Furthermore, an interdigitally parallel connection is proposed, which assists the PFCNS heater in achieving high temperature (84 °C) at a low voltage (4 V). This work provides a simple route for nylon-based TEs and promises satisfactory application in wearable sensors, power sources, and heaters.

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Human gait analysis is a standard method used for detecting and diagnosing diseases associated with gait disorders. Wearable technologies, due to their low costs and high portability, are increasingly being used in gait and other medical analyses. This paper evaluates the use of low-cost homemade textile pressure sensors to recognize gait phases. Ten sensors were integrated into stretch pants, achieving an inexpensive and pervasive solution. Nevertheless, such a simple fabrication process leads to significant sensitivity variability among sensors, hindering their adoption in precision-demanding medical applications. To tackle this issue, we evaluated the textile sensors for the classification of gait phases over three machine learning algorithms for time-series signals, namely, random forest (RF), time series forest (TSF), and multi-representation sequence learner (Mr-SEQL). Training and testing signals were generated from participants wearing the sensing pants in a test run under laboratory conditions and from an inertial sensor attached to the same pants for comparison purposes. Moreover, a new annotation method to facilitate the creation of such datasets using an ordinary webcam and a pose detection model is presented, which uses predefined rules for label generation. The results show that textile sensors successfully detect the gait phases with an average precision of 91.2% and 90.5% for RF and TSF, respectively, only 0.8% and 2.3% lower than the same values obtained from the IMU. This situation changes for Mr-SEQL, which achieved a precision of 79% for the textile sensors and 36.8% for the IMU. The overall results show the feasibility of using textile pressure sensors for human gait recognition.

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Textile and their composite-based functional sensors are extensively acknowledged and preferred detection platforms in recent times. Developing suitable methodologies for fabricating textile sensors can be achieved either by integration of conductive fibers and yarns into textiles using technologies such as weaving, knitting and embroidery; or by functionalization of textile materials with conductive nanomaterials/inks using printing or coating methods. Textile materials are gaining enormous attention for fabricating soft lab-on-fabric devices due to their unique features such as high flexibility, wear and wash resistance, mechanical strength and promising sensing performances. Owing to these collective properties, textile-based electrochemical transducers are now showcasing rapid and accurate electrical measurements towards real time point-of-care diagnostics and environmental monitoring applications. The present review provides a brief overview of key progress made in the field of developing textile materials and their composites-based electrochemical sensors and biosensors in recent years where electrode configurations are specifically based on either natural or synthetic fabrics. Different ways to fabricate and functionalize textiles for their application in electrochemical analysis are briefly discussed. The review ends with a conclusive note focusing on the current challenges in the fabrication of textile-based stable electrochemical sensors and biosensors.

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Textile-based sensors in the form of a wearable computing device that can be attached to or worn on the human body not only can transmit information but also can be used as a smart sensing device to access the mobile internet. These sensors represent a potential platform for the next generation of human-computer interfaces. The continuous emergence of new conductive materials is one of the driving forces for the development of textile sensors. Recently, a two-dimensional (2D) MXene material with excellent performance has received extensive attention due to its high conductivity, processability, and mechanical stability. In this paper, the synthesis of MXene materials, the fabrication of conductive textiles, the structural design of textile sensors, and the application of MXene-based textile sensors in the wearable field are reviewed. Furthermore, from the perspective of MXene preparation, wearability, stability, and evaluation standards, the difficulties and challenges of MXene-based textile sensors in the field of wearable applications are summarized and prospected. This review attempts to strengthen the connection between wearable smart textiles and MXene materials and promote the rapid development of wearable MXene-based textile sensors.

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We describe the development and preliminary evaluation of an innovative low-cost wearable device for gait analysis. We have developed a sensorized sock equipped with 32 piezoresistive textile-based sensors integrated in the heel and metatarsal areas for the detection of signals associated with the contact pressures generated during walking phases. To build the sock, we applied a sensing patch on a commercially available sock. The sensing patch is a stretchable circuit based on the resistive matrix method, in which conductive stripes, based on conductive inks, are coupled with piezoresistive fabrics to form sensing elements. In our sensorized sock, we introduced many relevant improvements to overcome the limitations of the classical resistive matrix method. We preliminary evaluated the sensorized sock on five healthy subjects by performing a total of 80 walking tasks at different speeds for a known distance. Comparison of step count and step-to-step frequency versus reference measurements showed a high correlation between the estimated measure and the real one.

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Among wearable e-textiles, conductive textile yarns are of particular interest because they can be used as flexible and wearable sensors without affecting the usual properties and comfort of the textiles. Firstly, this study proposed three types of piezoresistive textile sensors, namely, single-layer, double-layer, and quadruple-layer, to be made by the Jacquard processing method. This method enables the programmable design of the sensor's structure and customizes the sensor's sensitivity to work more efficiently in personalized applications. Secondly, the sensor range and coefficient of determination showed that the sensor is reliable and suitable for many applications. The dimensions of the proposed sensors are 20 × 20 cm, and the thicknesses are under 0.52 mm. The entire area of the sensor is a pressure-sensitive spot. Thirdly, the effect of layer density on the performance of the sensors showed that the single-layer pressure sensor has a thinner thickness and faster response time than the multilayer pressure sensor. Moreover, the sensors have a quick response time (<50 ms) and small hysteresis. Finally, the hysteresis will increase according to the number of conductive layers. Many tests were carried out, which can provide an excellent knowledge database in the context of large-area piezoresistive textile sensors using manufacturing by Jacquard processing. The effects of the percolation of CNTs, thickness, and sheet resistance on the performance of sensors were investigated. The structural and surface morphology of coating samples and SWCNTs were evaluated by using a scanning electron microscope. The structure of the proposed sensor is expected to be an essential step toward realizing wearable signal sensing for next-generation personalized applications.

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BACKGROUND: The Hexoskin is a smart shirt that can take continuous and objective measurements and could be part of a potential telemonitoring system. OBJECTIVE: The aim of this study was to determine the accuracy of the calibrated Hexoskin in measuring tidal volumes (TVs) in comparison to spirometry during various tasks. METHODS: In a cross-sectional study, the TV of 15 healthy subjects was measured while performing seven tasks using spirometry and the Hexoskin. These tasks were performed during two sessions; between sessions, all equipment was removed. A one-time spirometer-based calibration per task was determined in session 1 and applied to the corresponding task in both sessions. Bland-Altman analysis was used to determine the agreement between TV that was measured with the Hexoskin and that measured with spirometry. A priori, we determined that the bias had to be less than ±5%, with limits of agreement (LOA) of less than ±15%. Lung volumes were measured and had to have LOA of less than ±0.150 L. RESULTS: In the first session, all tasks had a median bias within the criteria (±0.6%). In the second session, biases were ±8.9%; only two tasks met the criteria. In both sessions, LOA were within the criteria in six out of seven tasks (±14.7%). LOA of lung volumes were greater than 0.150 L. CONCLUSIONS: The Hexoskin was able to correctly measure TV in healthy subjects during various tasks. However, after reapplication of the equipment, calibration factors were not able to be reused to obtain results within the determined boundaries. TRIAL REGISTRATION: Netherlands Trial Register NL6934; https://www.trialregister.nl/trial/6934.

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An e-textile mat with capacitive textile sensors was designed and manufactured to monitor body position and prevent decubitus ulcers in the case of bedridden people. The sensors were incorporated through a process of machine embroidery with electrically conductive threads. A new production method for the conductive threads is still expected to be developed, resulting in good conductive properties, high wear resistance and durability. Samples of five variants of motifs without cross-stitching were studied, and the capacity and electrical resistance were determined experimentally. A prototype of the e-textile mat was made with a motif showing the best ratio between the inserted thread and the measured capacity. A hardware solution and a software application for collecting, processing and visualising the received information were developed. Tests were performed in real conditions, which clearly showed that the designed e-textile mat could be successfully applied for non-invasive and continuous control of the position of the human body in a supine position to prevent decubitus ulcers.

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Monitoring scapular movements is of relevance in the contexts of rehabilitation and clinical research. Among many technologies, wearable systems instrumented by strain sensors are emerging in these applications. An open challenge for the design of these systems is the optimal positioning of the sensing elements, since their response is related to the strain of the underlying substrates. This study aimed to provide a method to analyze the human skin strain of the scapular region. Experiments were conducted on five healthy volunteers to assess the skin strain during upper limb movements in the frontal, sagittal, and scapular planes at different degrees of elevation. A 6 × 5 grid of passive markers was placed posteriorly to cover the entire anatomic region of interest. Results showed that the maximum strain values, in percentage, were 28.26%, and 52.95%, 60.12% and 60.87%, 40.89%, and 48.20%, for elevation up to 90° and maximum elevation in the frontal, sagittal, and scapular planes, respectively. In all cases, the maximum extension is referred to the pair of markers placed horizontally near the axillary fold. Accordingly, this study suggests interesting insights for designing and positioning textile-based strain sensors in wearable systems for scapular movements monitoring.

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