Autonomous Triboelectric Smart Textile Sensor for Vital Sign Monitoring.

Wearable smart textile sensors for monitoring vital signs are fast, noninvasive, and highly desirable for personalized health management to diagnose health anomalies such as cardiovascular diseases and respiratory dysfunction. Traditional biosignal sensors, with power consumption issues, constrain the use of wearable medical devices. This study introduces an autonomous triboelectric smart textile sensor (AUTS) made of reduced graphene oxide/manganese dioxide/polydimethylsiloxane (RGO-M-PDMS) and polytetrafluoroethylene (TEFLON)-knitted silver electrode, offering promise for vital sign monitoring with self-powering, flexibility, and wearability. The sensor exhibits impressive output performance, with a sensitivity of 7.8 nA/kPa, response time of ≈40 ms, good stability of >15,000 cycles, stretchability of up to 40%, and machine washability of >20 washes. The AUTS has been integrated to the TriBreath respiratory belt for monitoring respiratory signals and pulse strap for pulse signals concurrently at different body pulse points. These sensors wirelessly transmitted the acquired biosignals to a smartphone, demonstrating the potential of a self-powered and real-time vital sign monitoring system.

Integrating Wearable Textiles Sensors and IoT for Continuous sEMG Monitoring.

Surface electromyography is a technique used to measure the electrical activity of muscles. sEMG can be used to assess muscle function in various settings, including clinical, academic/industrial research, and sports medicine. The aim of this study is to develop a wearable textile sensor for continuous sEMG monitoring. Here, we have developed an integrated biomedical monitoring system that records sEMG signals through a textile electrode embroidered within a smart sleeve bandage for telemetric assessment of muscle activities and fatigue. We have taken an "Internet of Things"-based approach to acquire the sEMG, using a Myoware sensor and transmit the signal wirelessly through a WiFi-enabled microcontroller unit (NodeMCU; ESP8266). Using a wireless router as an access point, the data transmitted from ESP8266 was received and routed to the webserver-cum-database (Xampp local server) installed on a mobile phone or PC for processing and visualization. The textile electrode integrated with IoT enabled us to measure sEMG, whose quality is similar to that of conventional methods. To verify the performance of our developed prototype, we compared the sEMG signal recorded from the biceps, triceps, and tibialis muscles, using both the smart textile electrode and the gelled electrode. The root mean square and average rectified values of the sEMG measured using our prototype for the three muscle types were within the range of 1.001 ± 0.091 mV to 1.025 ± 0.060 mV and 0.291 ± 0.00 mV to 0.65 ± 0.09 mV, respectively. Further, we also performed the principal component analysis for a total of 18 features (15 time domain and 3 frequency domain) for the same muscle position signals. On the basis on the hierarchical clustering analysis of the PCA's score, as well as the one-way MANOVA of the 18 features, we conclude that the differences observed in the data for the different muscle types as well as the electrode types are statistically insignificant.

A fully textile-based, tunable, force and strain sensing resistor for e-textile applications.

This work presents a novel approach towards integrating electronic components with textiles, by successfully creating a fully textile-based element that is capable of detecting applied forces by variation in its resistance value. The fabrication of the device consists of a specialized siliconized conductive fabric, which is placed above and below a layer of switch fabric, which acts as a force sensor. In this paper, the effects of three different geometries are observed, as well as the washability of the device, along with tension testing. Μoreover, the device behavior is simulated as well as applied in a real-life scenario. The proposed element demonstrates a good dynamic range, high repeatability and stability, and minimal impact of washing, creating a great candidate for integration in e-textiles.

Flexible Iron-On Sensor Embedded in Smart Sock for Gait Event Detection.

Portable and wearable electronics for biomechanical data collection have become a growing part of everyday life. As smart technology improves and integrates into our lives, some devices remain ineffective, expensive, or difficult to access. We propose a washable iron-on textile pressure sensor for biometric data acquisition. Biometric data, such as human gait, are a powerful tool for the monitoring and diagnosis of ambulance and physical activity. To demonstrate this, our washable iron-on device is embedded into a sock and compared to gold standard force plate data. Biomechanical testing showed that our embedded sensor displayed a high aptitude for gait event detection, successfully identifying over 96% of heel strike and toe-off gait events. Our device demonstrates excellent attributes for further investigations into low-cost, washable, and highly versatile iron-on textiles for specialized biometric analysis.

Textile-Based Body Capacitive Sensing for Knee Angle Monitoring.

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.

Development of an Evaluation System for Transfer Care Skills Using Embroidered Body Pressure and Proximity Sensor.

OBJECTIVE: It is important to improve caregiving skills to help reduce the strain on inexperienced caregivers. Previous studies on quantifying caregiving skills have predominantly relied on expensive equipment, such as motion-capture systems with multiple infrared cameras or acceleration sensors. To overcome the cost and space limitations of existing systems, we developed a simple evaluation system for transfer care skills that uses capacitive sensors composed of conductive embroidery fibers. The proposed system can be developed with a few thousand US dollars. METHOD: The developed evaluation system was used to compare the seating position and velocity of a care recipient during transfers from a nursing-care bed to a wheelchair between groups of inexperienced and expert caregivers. To validate the proposed system, we compare the motion data measured by our system and the data obtained from a conventional three-dimensional motion-capture system and force plate. RESULTS: We analyze the relationship between changes in the center of pressure (CoP) recorded by the force plate and the center of gravity (CoG) obtained by the developed system. Evidently, the changes in CoP have a relation with the CoG. We show that the actual seating speed ([Formula: see text] measured by the motion-capture system is related to the speed coefficient calculated from our sensor output. A significant difference exists in [Formula: see text] between the inexperienced group and the physical therapists/occupational therapists' group. CONCLUSIONS: The proposed system can effectively estimate a caregiver's skill level in transferring patients from a bed to a wheelchair in terms of the seating position and velocity.

Tracing the Flu Symptom Progression via a Smart Face Mask.

Respiration and body temperature are largely influenced by the highly contagious influenza virus, which poses persistent global public health challenges. Here, we present a wireless all-in-one sensory face mask (WISE mask) made of ultrasensitive fibrous temperature sensors. The WISE mask shows exceptional thermosensitivity, excellent breathability, and wearing comfort. It offers highly sensitive body temperature monitoring and respiratory detection capabilities. Capitalizing on the advances in the Internet of Things and artificial intelligence, the WISE mask is further demonstrated by customized flexible circuitry, deep learning algorithms, and a user-friendly interface to continuously recognize the abnormalities of both the respiration and body temperature. The WISE mask represents a compelling approach to tracing flu symptom progression in a cost-effective and convenient manner, serving as a powerful solution for personalized health monitoring and point-of-care systems in the face of ongoing influenza-related public health concerns.

Seamless Weft Knit Vest with Integrated Needle Sensing Zone for Monitoring Shoulder Movement: A First Methodological Study.

The integration of textile-based flexible sensors and electronic devices has accelerated the development of wearable textiles for posture monitoring. The complexity of the processes required to create a complete monitoring product is currently reflected in three main areas. The first is the sensor production process, which is complex. Second, the integration of the sensor into the garment requires gluing or stitching. Finally, the production of the base garment requires cutting and sewing. These processes deteriorate the user experience and hinder the commercial mass production of wearable textiles. In this paper, we knitted a one-piece seamless knitted vest (OSKV) utilizing the one-piece seamless knitting technique and positioned an embedded needle sensing zone (EHSZ) with good textile properties and electrical performance for monitoring human shoulder activity. The EHSZ was knitted together with the OSKV, eliminating the need for an integration process. The EHSZ exhibited good sensitivity (GF = 2.23), low hysteresis (0.29 s), a large stretch range (200%), and excellent stability (over 300 cycles), satisfying the requirement to capture a wide range of deformation signals caused by human shoulder movements. The OSKV described the common vest process structure without the stitching process. Furthermore, OSKV fulfilled the demand for seamless and trace-free monitoring while effortlessly and aesthetically satisfying the knitting efficiency of commercial garments.

Textile Electronics with Laser-Induced Graphene/Polymer Hybrid Fibers.

The concept of wearables is rapidly evolving from flexible polymer-based devices to textile electronics. The reason for this shift is the ability of textiles to ensure close contact with the skin, resulting in comfortable, lightweight, and compact "always with you" sensors. We are contributing to this polymer-textile transition by introducing a novel and simple way of laser intermixing of graphene with synthetic fabrics to create wearable sensing platforms. Our hybrid materials exhibit high electrical conductivity (87.6 ± 36.2 Ω/sq) due to the laser reduction of graphene oxide and simultaneous laser-induced graphene formation on the surface of textiles. Furthermore, the composite created between graphene and nylon ensures the durability of our materials against sonication and washing with detergents. Both of these factors are essential for real-life applications, but what is especially useful is that our free-form composites could be used as-fabricated without encapsulation, which is typically required for conventional laser-scribed materials. We demonstrate the exceptional versatility of our new hybrid textiles by successfully recording muscle activity, heartbeat, and voice. We also show a gesture sensor and an electrothermal heater embedded within a single commercial glove. Additionally, the use of these textiles could be extended to personal protection equipment and smart clothes. We achieve this by implementing self-sterilization with light and laser-induced functionalization with silver nanoparticles, which results in multifunctional antibacterial textiles. Moreover, incorporating silver into such fabrics enables their use as surface-enhanced Raman spectroscopy sensors, allowing for the direct analysis of drugs and sweat components on the clothing itself. Our research offers valuable insights into simple and scalable processes of textile-based electronics, opening up new possibilities for paradigms like the Internet of Medical Things.

Evaluation of Novel Embroidered Textile-Electrodes Made from Hybrid Polyamide Conductive Threads for Surface EMG Sensing.

Recently, there has been an increase in the number of reports on textile-based dry electrodes that can detect biopotentials without the need for electrolytic gels. However, these textile electrodes have a higher electrode skin interface impedance due to the improper contact between the skin and the electrode, diminishing the reliability and repeatability of the sensor. To facilitate improved skin-electrode contact, the effects of load and holding contact pressure were monitored for an embroidered textile electrode composed of multifilament hybrid thread for its application as a surface electromyography (sEMG) sensor. The effect of the textile's inter-electrode distance and double layering of embroidery that increases the density of the conductive threads were studied. Electrodes embroidered onto an elastic strap were wrapped around the forearm with a hook and loop fastener and tested for their performance. Time domain features such as the Root Mean Square (RMS), Average Rectified Value (ARV), and Signal to Noise Ratio (SNR) were quantitatively monitored in relation to the contact pressure and load. Experiments were performed in triplicates, and the sEMG signal characteristics were observed for various loads (0, 2, 4, and 6 kg) and holding contact pressures (5, 10, and 20 mmHg). sEMG signals recorded with textile electrodes were comparable in amplitude to those recorded using typical Ag/AgCl electrodes (28.45 dB recorded), while the signal-to-noise ratios were, 11.77, 19.60, 19.91, and 20.93 dB for the different loads, and 21.33, 23.34, and 17.45 dB for different holding pressures. The signal quality increased as the elastic strap was tightened further, but a pressure higher than 20 mmHg is not recommended because of the discomfort experienced by the subjects during data collection.

Smart Shirt for Measuring Trunk Orientation.

Improper cycling posture is linked to a variety of spinal musculoskeletal diseases, including structural malformation of the spine and back discomfort. This paper presents a novel smart shirt integrated tri-axial gyroscope and accelerometer that can detect postural variation in terms of spinal curvature changes. To provide accurate feedback to the wearer and improve the wearer's correct movement, the garment is able to recognize trunk body posture. The gyroscope/accelerometer was placed around the upper and mid trunk of the user to record tri-axial angular velocity data. The device can also be used to help determine the trunk bending angle and monitor body postures in order to improve optimal orientation and position. The garment enables continuous measurement in the field at high sample rates (50 Hz), and the sensor has a large measurement range (16 g, 2000°/s). As electronic components are non-washable, instead of encapsulating them, a detachable module was created. In this, magnets are embedded in the jersey, and allow the positioning and removal of the sensor. The test results show that the average trunk-bending angle was 21.5°, and 99 percent of the observed angle fell within the standard (ranging from 8° to 35°). The findings demonstrate the feasibility of employing the smart shirt sensor to estimate trunk motions in the field on a regular basis.

Textile-Based Wearable Sensor for Skin Hydration Monitoring.

This research describes a wearable skin hydration sensor based on cotton textile to determine the state of hydration within the skin via impedance analysis. The sensor structure comprises a textile substrate, thermoplastic over-layer, conductive patterns, and encapsulant, designed for stable and reliable monitoring of the skin's impedance change in relation to hydration level. The porcine skin with different hydration levels was prepared as a model system of the skin, and the textile-based sensor carefully investigated the porcine skin samples' impedance characteristics. The impedance study reveals that (1) the total impedance of skin decreases as its hydration level increases, and (2) the impedance of the stratum corneum and epidermis layers are more dominantly affected by the hydration level of the skin than the dermis layer. Even after repetitive bending cycles, the impedance data of skin measured by the sensor exhibit a reliable dependence on the skin hydration level, which validates the flexibility and durability of the sensor. Finally, it is shown that the textile-based skin hydration sensor can detect various body parts' different hydration levels of human skin while maintaining a stable conformal contact with the skin. The resulting data are well-matched with the readings from a commercial skin hydration sensor.

Synthesis of Vapochromic Dyes Having Sensing Properties for Vapor Phase of Organic Solvents Used in Semiconductor Manufacturing Processes and Their Application to Textile-Based Sensors.

Two vapochromic dyes (DMx and DM) were synthesized to be used for textile-based sensors detecting the vapor phase of organic solvents. They were designed to show sensitive color change properties at a low concentration of vapors at room temperature. They were applied to cotton fabrics as a substrate of the textile-based sensors to examine their sensing properties for nine organic solvents frequently used in semiconductor manufacturing processes, such as trichloroethylene, dimethylacetamide, iso-propanol, methanol, n-hexane, ethylacetate, benzene, acetone, and hexamethyldisilazane. The textile sensor exhibited strong sensing properties of polar solvents rather than non-polar solvents. In particular, the detection of dimethylacetamide was the best, showing a color difference of 15.9 for DMx and 26.2 for DM under 300 ppm exposure. Even at the low concentration of 10 ppm of dimethylacetamide, the color change values reached 7.7 and 13.6, respectively, in an hour. The maximum absorption wavelength of the textile sensor was shifted from 580 nm to 550 nm for DMx and 550 nm to 540 nm for DM, respectively, due to dimethylacetamide exposure. The sensing mechanism was considered to depend on solvatochromism, the aggregational properties of the dyes and the adsorption amounts of the solvent vapors on the textile substrates to which the dyes were applied. Finally, the reusability of the textile sensor was tested for 10 cycles.

Smart Graphene Nanoplatelet Strain Sensor for Natural Frequency Sensing of Stainless Steel (SS304) and Human Health Monitoring.

The main purpose of this article is to monitor the natural frequency of stainless steel (SS304) with and without defect by spray-coated smart graphene nanoplatelet (GNPs)-doped poly (methyl methacrylate) (PMMA) nanocomposite strain sensor and human health by smart Lycra denim textile sensor. Methods such as impact hammer test and NI-daq, finite element method (FEM) simulation by Abaqus 6.12, and fast Fourier transform (FFT) study were applied for frequency monitoring of SS304. For human health monitoring, edema disease inspection, cough, and biceps locomotion were studied by graphene sol-gel textile sensor. We report eight sensors fabricated by scotch tape exfoliation method and their sensitivity was checked in terms of gauge factor (GF). The highest and lowest GF-based sensors were checked for sensitivity in the defect (hole) specimen. These sensors were used to sense the natural frequency of SS304 at three different positions in the cantilever beam. The same quantity of GNPs was used for making Lycra denim textile sensors for human health monitoring. The Lycra denim textile sensor showed a 216% change in resistance in the left calf muscle, which is less than right leg flexibility, indicating good sensitivity. In addition, the textile sensor helped in sensing coughing and biceps monitoring. The ease in fabrication and high sensitivity demonstrate the potential ability of GNPs for futuristic smart material for structural and human health monitoring.

Effects of Fe Staple-Fiber Spun-Yarns and Correlation Models on Textile Pressure Sensors.

As an aspect of intelligent clothing, e-textile sensors can flexibly sense and transmit information about human bodies and environments. However, difficulties relating to their technology and the variation in textile materials employed in their manufacture still limit their ability to analyze and be applied. The authors' previous publication deployed a pressure sensor with warp-knitted spacer fabrics, wet-knitted fabrics, Ag-yarns, and Fe-yarns. An equivalent circuit analyzed the resistance behavior with some effects of the Ag-coated twisted yarns. In the present paper, the authors continue to evaluate the correlation model R-ε and the effects of the Fe staple-fiber spun yarns in detail. Together, the two studies provide an extensive understanding of the textile-related elements that affect pressure sensors. In addition, the process and the analysis (correlation model) could bring the textile sensors here developed close to the manufacturing stage, particularly for high precision/adjustable applications. We also develop a simple touch sensor matrix to demonstrate the potential of the sensor and the analyzing method.

Development of a low-cost textile sensor based insole to monitor foot pressure of diabetic patients.

A common but preventable complication of diabetes is diabetic foot ulcer. If appropriate care is not provided such foot lesions progress to the most severe diabetic foot complication, like infection, gangrene, amputation and even death. Diabetic neuropathy results abnormal planter pressure points under the foot and triggers the tendency of foot ulcer. The aim of this paper is to present the development of a low cost, power efficient, soft, lightweight and simple in-shoe planter pressure measurement system. The system is capable to determine the average static pressure under ball and heel of the foot. The insole is comfortable due to the use of textile pressure sensor and its simple data acquisition method makes operation easy for the users. An experiment with 10 participants with and without diabetes was carried out to observe the outcome of the system. The practical implication of this study is to minimise the damage caused by foot ulcer by determining the pressure abnormality at earliest with a fully developed cost effective design. The system is capable to identify the difference in average planter pressure values in different groups of participants. To monitor the foot health proactively, the proposed system is found to be a useful device and can successfully scan the planter pressure under ball and heel of the foot.

Silver Conductive Threads-Based Embroidered Electrodes on Textiles as Moisture Sensors for Fluid Detection in Biomedical Applications.

Wearable sensors have become part of our daily life for health monitoring. The detection of moisture content is critical for many applications. In the present research, textile-based embroidered sensors were developed that can be integrated with a bandage for wound management purposes. The sensor comprised an interdigitated electrode embroidered on a cotton substrate with silver-tech 150 and HC 12 threads, respectively, that have silver coated continuous filaments and 100% polyamide with silver-plated yarn. The said sensor is a capacitive sensor with some leakage. The change in the dielectric constant of the substrate as a result of moisture affects the value of capacitance and, thus, the admittance of the sensor. The moisture sensor's operation is verified by measuring its admittance at 1 MHz and the change in moisture level (1-50) µL. It is observed that the sensitivity of both sensors is comparable. The identically fabricated sensors show similar response and sensitivity while wash test shows the stability of sensor after washing. The developed sensor is also able to detect the moisture caused by both artificial sweat and blood serum, which will be of value in developing new sensors tomorrow for smart wound-dressing applications.

Conditions for CNT - Coated Textile Sensors Applied to Wearable Platforms to Monitor Limb Joint Motion.

Despite recent research on joint motion measurement to monitor human body movement, current measurement techniques and tools have significant limitations, including requiring large space for measurement and causing discomfort in test subjects wearing motion sensors. Our study aims, first, to develop carbon nanotube (CNT)-based textile joint motion sensors. Second, ours study aims to identify the most suitable CNT-based sensor structure and attachment method for use on a wearable platform during general exercise speeds. Lastly, we used these sensors on the human body, using sleeves and legs to find the most stable location, and we used the CNT-based sensor condition to monitor joint motions. We utilized our CNT-based sensor, which has proper elasticity as well as conductivity, and applied it to the elbow and knee joints. Based on the strain gauge principle, we monitored the variance of electric resistance that occurred when the CNT-based sensor was stretched due to limb motion. Our study tested 48 types of sensors. These sensors were applied to the CNT using different base knit textiles as well as different attachment methods, layers, sensor lengths, and sensor widths. The four most successful sensor types, which showed superior efficacy over the others in joint motion measurement, were selected for further study. These four sensors were then used to measure the elbow and knee joint motions of human subjects by placing them on different locations on sleeves and legs. The CNT knit textile sensors best suited to measuring joint motions are those with a double-layered CNT knit and 5 cm long × 0.5 cm or 1 cm wide sensors attached to a polyester¬-based knit using a welding method. The best position for the sensor to more stably monitor joint motions was the "below hinge position" from the elbow or knee hinge joint. Our study suggests an alternative strategy for joint-motion measurement that could contribute to the development of more comfortable and human-friendly methods of human limb motion measurement.

Bio-Inspired Electronic Textile Yarn-Based NO2 Sensor Using Amyloid-Graphene Composite.

Graphene-based e-textile gas sensors have received significant attention as wearable electronic devices for human healthcare and environmental monitoring. Theoretically, more the attached graphene on the devices, better is the gas-sensing performance. However, it has been hampered by poor adhesion between graphene and textile platforms. Meanwhile, amyloid nanofibrils are reputed for their ability to improve adhesion between materials, including between graphene and microorganisms. Despite that fact, there has been no attempt to apply amyloid nanofibrils to fabricate graphene-based e-textiles. By biomimicking the adhesion ability of amyloid nanofibrils, herein, we developed a graphene-amyloid nanofibril hybrid e-textile yarn (RGO/amyloid nanofibril/CY) for the detection of NO2. Compared to traditional e-textile yarn, the RGO/amyloid nanofibril/CY showed better performance in response time, sensing efficiency, sensitivity, and selectivity for NO2. Last, we suggested a practical use of RGO/amyloid nanofibril/CY combined with a light-emitting diode as a wearable e-textile gas sensor.

Colorimetric Textile Sensor for the Simultaneous Detection of NH3 and HCl Gases.

For the immediate detection of strong gaseous alkalis and acids, colorimetric textile sensors based on halochromic dyes are highly valuable for monitoring gas leakages. To date, colorimetric textile sensors for dual-gas detection have usually been fabricated by electrospinning methods. Although nanofibrous sensors have excellent pH sensitivity, they are difficult to use commercially because of their low durability, low productivity, and high production costs. In this study, we introduce novel textile sensors with high pH sensitivity and durability via a facile and low-cost screen-printing method. To fabricate these textiles sensors, Dye 3 and RhYK dyes were both incorporated into a polyester fabric. The fabricated sensors exhibited high detection rates (<10 s) and distinctive color changes under alkaline or acidic conditions, even at low gas concentrations. Furthermore, the fabricated sensors showed an outstanding durability and reversibility after washing and drying and were confirmed to contain limited amounts of hazardous materials. Thus, our results show that the fabricated textile sensors could be used in safety apparel that changes its color in the presence of harmful gases.