Explore the vast range of titles available.

Wearable technology applications have experienced remarkable development and advancements, with soft and stretchable strain sensors playing a significant role in this progress. Despite the promising potential of combed‐shaped interdigital capacitive strain sensors in wearable electronics, several challenges exist, including limited stretchability, universal mass fabrication, and seamless integration into diverse clothing parts. This study presents a textile knitted interdigital capacitive sensor that incorporates stretchable conductive yarn, produced using textile twisting technology, to achieve stretchability and adaptability, allowing seamless conformation to human body movements and textile materials. The fabrication process involves embedding the interdigital electrodes and interconnections directly into the fabric through textile knitting technology, ensuring robust integration. Furthermore, this work presents opportunities for commercializing the stretchable interdigital strain sensor through a low‐cost and mass production strategy. Electromechanical characterization demonstrates exceptional performance with high stretchability (≈230%), excellent linearity (R2 = 0.997), a gauge factor (GF) of −0.68 representing relative capacitance change, and a rapid response time of 66 ms. To validate the usability of sensors in wearable technology, a knee brace application is employed to investigate capacitance changes during walking and cycling exercises. This approach will accelerate the accessibility of wearable stretchable interdigital sensors for all. This study presents a novel textile knitted interdigital capacitive strain sensor for wearable technologies. The knitting technology fabrication allows for cost‐effective mass production of these interdigital sensors, making them accessible for various wearable electronic applications. The sensor incorporates stretchable conductive yarn, which provides high stretchability and adaptability to human body movements and textile materials.

Wearable pressure sensors for specific applications are in growing demand due to their flexibility, sensitivity, low power consumption, and portability. Flexible capacitive pressure sensors with micro‐structured dielectric layers have shown promise in meeting these demands by tuning the dielectric geometry and material properties. Finite Element Analysis (FEA) based on Finite Element Method (FEM) predicts the response of a sensor under various inputs and parameters and hence facilitates the design and development of sensors. By employing FEA, the performance pressure sensors can be predicted based on microstructures. A textile‐based capacitive pressure sensor is presented, enhanced with a triangular prism micro‐structure in the dielectric layer, improving sensitivity by up to four orders higher than its non‐structured counterparts. The sensor demonstrates a remarkable sensitivity of 5.52% kPa−¹(0.24–50 kPa), with linearity (R2 = 0.981), a wide sensing range (0.24–330 kPa), and mechanical stability >1000 cycles. Its use is demonstrated in a 4‐channel force myography (FMG) armband, validated across five subjects with an average gesture recognition accuracy of 92% for common hand gestures. The applications of the device are further demonstrated to control a prosthetic hand and operate a game, paving the way for advancements in smart wearable technologies within HMI applications. This study introduces a textile‐based capacitive pressure sensor featuring a triangular prism microstructure, which significantly enhances sensitivity to 5.52% kPa−¹ and supports a wide sensing range up to 330 kPa. The sensor's performance is validated in a 4‐channel capacitive pressure‐based force myography (cFMG) armband for gesture recognition, extending to real‐time control of a prosthetic hand and gaming, advancing human‐machine interface applications.

The world’s population is aging: the expansion of the older adult population with multiple physical and health issues is now a huge socio-economic concern worldwide. Among these issues, the loss of mobility among older adults due to musculoskeletal disorders is especially serious as it has severe social, mental and physical consequences. Human body joint monitoring and early diagnosis of these disorders will be a strong and effective solution to this problem. A smart joint monitoring system can identify and record important musculoskeletal-related parameters. Such devices can be utilized for continuous monitoring of joint movements during the normal daily activities of older adults and the healing process of joints (hips, knees or ankles) during the post-surgery period. A viable monitoring system can be developed by combining miniaturized, durable, low-cost and compact sensors with the advanced communication technologies and data processing techniques. In this study, we have presented and compared different joint monitoring methods and sensing technologies recently reported. A discussion on sensors’ data processing, interpretation, and analysis techniques is also presented. Finally, current research focus, as well as future prospects and development challenges in joint monitoring systems are discussed.

Textile-based flexible pressure sensors have attracted considerable attention in wearable sensing applications due to their good comfort and mechanical compatibility. However, their sensitivity usually exhibits a nonlinear dependence on pressure, while a compact analytical framework with interpretable physical parameters is still lacking. In this work, a simplified physical model based on lumped effective parameters was established based on the evolution of fiber–conductive particle contacts, and an expression describing the sensitivity–pressure relationship was derived. The model indicates that the sensitivity is mainly governed by an electrical parameter α and a mechanical parameter ratio Eb/Ex, and captures the dominant nonlinear decrease in sensitivity with increasing pressure. To verify the applicability of the model, the effects of conductive particle loading, filler type, surface treatment, sensing-layer area, weave structure, and layer number on the sensor response were systematically investigated. In addition, comparison between model-based calculation and experiment in the low- and medium-pressure range gave RMSE values of 0.0040 and 0.0056, and MRE values of 27.6% and 13.4% for the single-layer and four-layer structures, respectively. These results show that the proposed framework captures the main trends of the sensitivity–pressure behavior and provides a physically interpretable basis for discussing how structural and material factors regulate sensor response. This work offers a useful framework for understanding the structure–property relationship of textile-based piezoresistive pressure sensors and may provide preliminary guidance for the design of customized sensors in wearable healthcare and soft robotics applications.

This paper presents a system dedicated to monitoring the heart activity parameters using Electrocardiography (ECG) mobile devices and a Wearable Heart Monitoring Inductive Sensor (WHMIS) that represents a new method and device, developed by us as an experimental model, used to assess the mechanical activity of the hearth using inductive sensors that are inserted in the fabric of the clothes. Only one inductive sensor is incorporated in the clothes in front of the apex area and it is able to assess the cardiorespiratory activity while in the prior of the art are presented methods that predict sensors arrays which are distributed in more places of the body. The parameters that are assessed are heart data-rate and respiration. The results are considered preliminary in order to prove the feasibility of this method. The main goal of the study is to extract the respiration and the data-rate parameters from the same output signal generated by the inductance-to-number convertor using a proper algorithm. The conceived device is meant to be part of the “wear and forget” equipment dedicated to monitoring the vital signs continuously.

Wearable sweat biosensors for noninvasive monitoring of health parameters have attracted significant attention. Having these biosensors embedded in textile substrates can provide a convenient experience due to their soft and flexible nature that conforms to the skin, creating good contact for long-term use. These biosensors can be easily integrated with everyday clothing by using textile fabrication processes to enhance affordable and scalable manufacturing. Herein, a flexible electrochemical glucose sensor that can be screen-printed onto a textile substrate has been demonstrated. The screen-printed textile-based glucose biosensor achieved a linear response in the range of 20–1000 µM of glucose concentration and high sensitivity (18.41 µA mM−1 cm−2, R2 = 0.996). In addition, the biosensors show high selectivity toward glucose among other interfering analytes and excellent stability over 30 days of storage. The developed textile-based biosensor can serve as a platform for monitoring bio analytes in sweat, and it is expected to impact the next generation of wearable devices.

Skin pH can be used for monitoring infections in a healing wound, the onset of dermatitis, and hydration in sports medicine, but many challenges exist in integrating conventional sensing materials into wearable platforms. We present the development of a flexible, textile-based, screen-printed electrode system for biosensing applications, and demonstrate flexible polyaniline (PANI) composite-based potentiometric sensors on a textile substrate for real-time pH measurement. The pH response of the optimized PANI/dodecylbenzene sulfonic acid/screen-printing ink composite is compared to electropolymerized and drop-cast PANI sensors via open circuit potential measurements. High sensitivity was observed for all sensors between pH 3–10, with a composite based on PANI emeraldine base, demonstrating sufficient response time and a linear sensitivity of −27.9 mV/pH. This exceeded prior flexible screen-printed pH sensors in which all parts of the sensor, including the pH sensing material, are screen-printed. Even better sensitivity was observed for a PANI emeraldine salt composite (−42.6 mV/pH), although the response was less linear. Furthermore, the sensor was integrated into a screen-printed microfluidic channel demonstrating sample isolation during measurement for wearable, micro cloth-based analytical devices. This is the first fully screen-printed flexible PANI composite pH sensor demonstrated on a textile substrate that can additionally be integrated with textile-based microfluidic channels.

The integration of agriculture and Internet of Things (IoT) technology has transformed traditional farming into data-driven, automated, and highly interactive systems. Central to this evolution are sensor platforms that monitor soil conditions and environmental parameters such as moisture, temperature, pH, nutrients, and pollutants. Recent progress in flexible electronics and smart functional materials has created new opportunities for developing adaptable sensor systems suited to dynamic agricultural applications. Despite these advancements, the use of geotextiles as soil-sensing platforms remains largely unexplored. This review traces the shift from conventional rigid soil sensors to flexible and potentially geotextile-based systems, assessing their roles in IoT-enabled agricultural applications. While soil sensors are generally discussed under separate headings, the review integrates them under the common themes, including material selection, fabrication methods, testing methodologies, energy management strategies, and IoT connectivity. By identifying common materials, design principles, and manufacturing techniques across various soil sensors, the review proposes a synthesis framework that supports multi-sensor integration. Extending this integrative approach to geotextile-based structures envisions the realization of flexible, large-area, and adaptive soil sensing platforms that could enable next-generation of sustainable and smart precision agriculture.

Smart textile sensors have been gaining popularity as alternative methods for the continuous monitoring of human motion. Multiple methods of fabrication for these textile sensors have been proposed, but the simpler ones include stitching or embroidering the conductive thread onto an elastic fabric to create a strain sensor. Although multiple studies have demonstrated the efficacy of textile sensors using the stitching technique, there is almost little to no information regarding the fabrication of textile strain sensors using the embroidery method. In this paper, a design guide for the fabrication of an embroidered resistive textile strain sensor is presented. All of the required design steps are explained, as well as the different embroidery design parameters and their optimal values. Finally, three embroidered textile strain sensors were created using these design steps. These sensors are based on the principle of superposition and were fabricated using a stainless-steel conductive thread embroidered onto a polyester–rubber elastic knit structure. The three sensors demonstrated an average gauge factor of 1.88±0.51 over a 26% working range, low hysteresis (8.54±2.66%), and good repeatability after being pre-stretched over a certain number of stretching cycles.

Textile-based sensors fabricated using the direct-coating method are the appropriate choice to meet the aspects of flexibility, non-invasiveness, and lightness for continuous monitoring of the human body. The characteristics of the sensor substrate are directly influenced by factors such as the type of weave, thread fineness, fabric density, and the type of polymeric constituent fibers. The fabric used as the sensor substrate, fabricated using the direct-coating method, must be capable of retaining the electrode paste solution, which has higher viscosity, on one surface of the fabric to avoid short circuits during the fabrication process. However, during its application, this fabric should allow the easy passage of analyte solutions with low viscosity as much as possible. Hence, an appropriate fabric construction is required to serve as the substrate for textile-based sensors to ensure the success of the fabrication process and the effectiveness of the resulting sensor’s performance. The development of the structural design of the fabric to be used as a substrate for non-invasive biosensors with a multilayer concept is carried out by weaving and sewing processes utilizing polyester-viscose fibers. During the production process, variations are applied, such as weft yarn density, the characterization of wetting time, absorption rate, maximum wetted radius, spreading speed, and accumulative one-way transport index. The most suitable fabric for use as a substrate for non-invasive biosensors with a multilayer concept, such as in this research, is a fabric with a weft thread density of 70 strands per inch, along with the addition of an analyte transfer thread configuration.